Human pregnancies last 40 weeks on average. Preterm births, defined as live births before 37 weeks, occur in about one in ten pregnancies. Being born too early is the main cause of a number of diseases and death in newborn babies.

Preterm births are further divided into those that happen early – before 34 weeks – and those that happen late – between 34 and 37 weeks. There are also differences between preterm births in which the amniotic sac ruptures before or after the start of labor.

Although several factors can lead to spontaneous preterm birth, bacteria getting into the amniotic fluid around the fetus are a well-known trigger. These bacteria usually come from the vagina. In the past, researchers have studied the number and types of bacteria in the vagina of people who had a normal pregnancy and those that had a preterm birth to predict who is more at risk of preterm birth.

However, predictions based only on data about bacteria have been less useful so far. Instead, it might be better to investigate a person’s immune response during pregnancy. Shaffer et al. addressed this gap by asking whether measuring the levels of proteins involved in the immune response could help predict preterm births.

Shaffer et al. collected vaginal fluids from 739 individuals of predominately African American ethnicity with an average BMI of 28.7 – representing a population at high risk for spontaneous preterm birth. The swabs were taken at multiple points during their pregnancy, and 31 different immune-related proteins in those fluids were measured. The researchers further noted whether these individuals had a normal or a preterm birth.

The data showed that, compared to normal births, preterm births are associated with higher levels of proteins that attract white blood cells and promote inflammation, such as IL-6 and IL-1β. Vaginal fluids from individuals who went on to have an early preterm birth where the amniotic sac ruptured before labor, contained lower levels of proteins known as defensins, which defend the body from bacteria.

With these new data from vaginal swabs, Shaffer et al. could make better predictions about the likelihood of preterm birth in general and early preterm birth with the amniotic sac ruptured before labor. For the latter scenario, the predictions were not improved when combining immune protein data with other characteristics of the pregnant person, such as age.

These findings suggest that clinicians may be able to use measurements of immune-related proteins to help predict preterm births, so that pregnant individuals at high risk can receive extra care. Further research will have to validate the data and determine whether the findings apply more widely.

Preterm birth, defined as live birth before 37 weeks of gestation (American College of Obstetricians and Gynecologists, 2021), afflicts 1 of every 10 children born worldwide (Chawanpaiboon et al., 2019; Martin and Hamilton, 2021). The economic burden of preterm birth amounts to more than $25.2 billion in healthcare costs annually in the United States alone (Waitzman et al., 2021). Two-thirds of preterm births occur spontaneously (i.e., spontaneous preterm birth [sPTB]) (Goldenberg et al., 2008), while the remainder are due to evident clinical conditions (e.g., preeclampsia and intrauterine growth restriction) that jeopardize maternal–fetal well-being and require medically indicated delivery (i.e., iatrogenic preterm birth) (Goldenberg et al., 2008; Romero et al., 2014a). sPTB can be further subdivided into spontaneous preterm labor with intact membranes (sPTL) and preterm prelabor rupture of membranes (PPROM) (Goldenberg et al., 2008). The pathogenesis of sPTL and PPROM can include local inflammatory processes (Romero et al., 2014a); yet, each is considered a syndrome with distinct underlying mechanisms of disease (Goldenberg et al., 2008; Romero et al., 2014a) and thus requiring different clinical managements (American College of Obstetricians and Gynecologists, 2016; Dvorakova and Ivankova, 2020). Therefore, research focused on the prediction and prevention of sPTB should account for the distinct inflammatory nature of sPTL and PPROM.

Multiple attempts have been made to predict sPTB using data from noninvasive sampling coupled with omics platforms such as genomics (Frey et al., 2016; Modi et al., 2017; Modi et al., 2018; Jain et al., 2022), transcriptomics (Ngo et al., 2018; Jehan et al., 2020; Peterson et al., 2020; Tarca et al., 2021; Camunas-Soler et al., 2022), and proteomics (Peterson et al., 2020; Jehan et al., 2020; Tarca et al., 2021; Tiensuu et al., 2022). Yet, to date, assessment of cervical length remains the strongest and most cost-effective predictor of sPTB: women with a sonographic short cervix (≤ 25 mm) are sixfold more likely to deliver a preterm neonate (Iams et al., 1996), and tailored treatment with natural progesterone reduces such risk by half (Fonseca et al., 2007; Hassan et al., 2011; Romero et al., 2014b; Romero et al., 2016; Romero et al., 2017; Conde-Agudelo et al., 2018; Romero et al., 2018). Indeed, personalized cervical length assessment that accounts for maternal characteristics and obstetrical history was shown to improve prediction relative to raw cervical length data (Gudicha et al., 2021); however, additional biomarkers are still needed to further increase prediction performance. Growing evidence has fostered the hypothesis that cervical disease is associated with changes in the vaginal ecosystem (Kindinger et al., 2017; Witkin et al., 2019; Di Paola et al., 2020; Gerson et al., 2020). Thus, intensive investigation has focused on the vaginal microbiome and its potential utility for predicting sPTB (Donders et al., 2009; DiGiulio et al., 2015; Kindinger et al., 2017; Freitas et al., 2018; Fettweis et al., 2019; Odogwu et al., 2021; Payne et al., 2021; Flaviani et al., 2021; Pruski et al., 2021; Kumar et al., 2021). However, models utilizing vaginal microbiome data alone have displayed weak predictive power (Freitas et al., 2018; Kumar et al., 2021; Pruski et al., 2021), potentially due to sample size, sequencing depth, and ethnicity-driven differences in microbial community profile. Recent models, however, have leveraged vaginal host–microbe interactions by incorporating the determination of immune mediators, which improved the prediction of sPTB (Elovitz et al., 2019; Fettweis et al., 2019; Pruski et al., 2021; Kumar et al., 2021). Nonetheless, an extensive interrogation of the vaginal soluble immune response (i.e., the vaginal immunoproteome), with consideration of the distinction between sPTL and PPROM cases, has not been undertaken.

Herein, we conducted the largest assessment, based on the study’s scale, longitudinal nature, and depth of immunological mediators evaluated, of the vaginal immunoproteome during uncomplicated and complicated pregnancies. Importantly, our determinations were performed in vaginal samples collected during all three trimesters and considered sPTB, including its two subsets (i.e., sPTL and PPROM), as well as the timing of delivery (i.e., early and late sPTB). Furthermore, the immunological mediators evaluated were selected for their relevance to key biological processes in the vaginal ecosystem. Additionally, we used machine learning approaches and cross-validation to generate and assess predictive models for sPTL and PPROM in our high-risk population.

The vaginal ecosystem includes cellular and soluble components that maintain homeostasis and provide defense against potential pathogens (Donders et al., 2003; Lee et al., 2015; Smith and Ravel, 2017; Mei et al., 2019; Hezelgrave et al., 2020; Monin et al., 2020). While the cellular fraction has been poorly investigated, the soluble components have been well characterized during pregnancy (Wennerholm et al., 1998; Donders et al., 2003; Chandiramani et al., 2012; Amabebe et al., 2018; Ashford et al., 2018; Fettweis et al., 2019; Witkin et al., 2019; Florova et al., 2021; Chan et al., 2022). The soluble fraction includes cytokines, chemokines, antimicrobial peptides/proteins, metabolites, antibodies, and complement components, among others, (Donders et al., 2003; Wei et al., 2010; Tribe, 2015; Oh et al., 2019; Pruski et al., 2021; Delgado-Diaz et al., 2022). It is likely that the vaginal soluble fraction mirrors the three inflammatory phases described at the maternal-fetal interface: a pro-inflammatory profile accompanies the process of implantation, an anti-inflammatory state is maintained throughout the majority of gestation, and an inflammatory milieu is associated with the onset of parturition (Gomez-Lopez et al., 2010; Erlebacher, 2013). Yet, such a concept has not been established and thus remains to be proven. Herein, we report the largest longitudinal investigation of the vaginal immunoproteome from 8 weeks (i.e., after implantation) to term (collected prior to the onset of parturition), showing that several immune mediators are modulated throughout normal gestation. Specifically, we report that, while multiple innate-derived pro-inflammatory mediators undergo a steady reduction, T cell-associated cytokines and the pro-angiogenic factor VEGF increase throughout gestation. These findings suggest that the vaginal immunoproteome undergoes a modest modulation to help ensure that a homeostatic microenvironment is maintained. Our results are consistent with the prevailing hypothesis that immune homeostasis is required to maintain a successful pregnancy until delivery, and that a breakdown of such homeostasis is implicated as a mechanism of disease for sPTB (Gomez-Lopez et al., 2020; Gomez-Lopez et al., 2021; Gomez-Lopez et al., 2022a). Consistent with this hypothesis, systems biology approaches using proteomics, cytomics, and transcriptomics have conceptualized an immunological clock for pregnancy and have suggested that the early detection of its malfunction may allow for the prediction of sPTB (Aghaeepour et al., 2017; Aghaeepour et al., 2018; Gomez-Lopez et al., 2019c; Ghaemi et al., 2019; Peterson et al., 2020; Tarca et al., 2021; Stelzer et al., 2021; Gomez-Lopez et al., 2022b). Herein, we built upon this concept by longitudinally exploring the vaginal immunoproteome of women who ultimately underwent sPTB.

Our first set of results showed that multiple pro-inflammatory cytokines, particularly IL-6 and IL-1β, were upregulated in the vaginal fluid of women who ultimately underwent sPTL or PPROM compared to women who delivered at term. Interleukin-6 is a highly pleiotropic cytokine that participates in acute and chronic inflammation, hematopoiesis, and other developmental and physiological processes (Jones and Jenkins, 2018). Importantly, IL-6 not only regulates the innate immune response but also participates in the transition to a sustained adaptive immune response, which has made this cytokine and its family attractive targets for immunotherapies (Jones and Jenkins, 2018). Moreover, IL-6 regulates the recruitment and activity of leukocytes and may thus be an important upstream regulator of the vaginal chemokine response observed in women with sPTB in the current study. Interleukin-6 also plays a central role in antimicrobial/antiviral immunity (Jones and Jenkins, 2018). Indeed, IL-6 is the established biomarker for the diagnosis of acute intra-amniotic inflammation (Yoon et al., 2001), the most well-established causal link to preterm labor and birth (Romero et al., 2006b; Romero et al., 2007; Goldenberg et al., 2008; Romero et al., 2014a). Consistent with the pro-inflammatory functions of IL-6, IL-1β is also an acute inflammatory cytokine that may even precede the upregulation of IL-6 (Hazuda et al., 1988; Cahill and Rogers, 2008). Yet, IL-1β is synthesized as a zymogen and therefore requires processing via specific intracellular machinery (i.e., the NLRP3 inflammasome) to be released in its mature and bioactive form (Kostura et al., 1989). Notably, we have provided in vivo and in vitro demonstrations that the tissues surrounding the amniotic cavity (i.e., the chorioamniotic membranes), as well as tissues of the upper FRT (e.g., uterine tissues), express the components of the NLRP3 inflammasome (Plazyo et al., 2016; Gomez-Lopez et al., 2017; Gomez-Lopez et al., 2018; Gomez-Lopez et al., 2019b; Gomez-Lopez et al., 2019a; Faro et al., 2019; Motomura et al., 2020; Motomura et al., 2021; Motomura et al., 2022). In fact, in vivo administration of LPS or alarmins, pathogen-associated molecular patterns, and danger-associated molecular patterns that can activate the NLRP3 inflammasome (Swanson et al., 2019) results in the processing of active caspase-1 and the subsequent release of mature IL-1β, leading to preterm labor and birth (Gomez-Lopez et al., 2019b; Faro et al., 2019; Motomura et al., 2020; Motomura et al., 2021; Motomura et al., 2022). In line with these results, the intra-amniotic infusion of IL-1β triggers the common pathway of parturition and leads to preterm birth in non-human primates (Gravett et al., 1994; Witkin et al., 1994; Baggia et al., 1996; Vadillo-Ortega et al., 2002; Sadowsky et al., 2006; Presicce et al., 2015) and mice (Yoshimura and Hirsch, 2005). Moreover, the blockade of either of these pro-inflammatory cytokines through natural inhibitors (e.g., IL-1RA [Romero and Tartakovsky, 1992b]) or neutralizing antibodies (e.g., anti-IL-6R [Wakabayashi et al., 2013; Farias-Jofre et al., 2023]) rescues preterm labor and birth. Thus, given their stereotypical role in acute inflammation, the elevated vaginal concentrations of IL-6 and IL-1β described herein may therefore point to a local inflammatory response that precedes intra-amniotic inflammation that is conventionally associated with sPTB. Whether this local increase represents an aberrant host response to vaginal commensals, the sudden expansion of an opportunistic pathogen, or some other host–microbe interaction requires further investigation. Nonetheless, the above-described evidence further supports IL-6 and IL-1β as master regulators of the onset of preterm parturition, as has been previously demonstrated (Romero et al., 2006a; Robertson et al., 2010; Gomez‐Lopez et al., 2016; Romero et al., 1989; Romero et al., 1992a). It is worth noting that we report distinct patterns of the vaginal immunoproteome between early and late preterm delivery for both sPTB subsets, with the most significant increases observed in women with early PPROM or late sPTL. Thus, these findings provide additional insight into the differing dynamics underlying these two sPTB subsets (Fortunato et al., 1999; Erez et al., 2009; Polettini et al., 2014; Capece et al., 2014; Dutta et al., 2016; Dvorakova et al., 2017; Menon and Richardson, 2017). Furthermore, these findings could be partially explained by the genetic predisposition observed in the fetal cord blood of women who undergo PPROM, which displays rare mutations of genes involved in the negative regulation of innate immune activation (Modi et al., 2017; Strauss and Pearson, 2018); however, additional research is required to investigate the maternal contribution to such a predisposition to undergo PPROM. Regardless of the differing mechanisms that can drive sPTL and PPROM, our data support a shared vaginal immune signature that accompanies inflammation-associated sPTB, potentially reflecting the inflammatory status of the amniotic cavity. This observation is consistent with the concept of a ‘common pathway of labor’ (Romero et al., 2014a) and indicates that it is important to distinguish between changes in vaginal immune mediators that are driven by labor and those that are specific to the disease subset (i.e., sPTL vs. PPROM).

Another finding of the current study was the observed increase in the vaginal concentrations of chemokines implicated in leukocyte recruitment, i.e., CCL2, CCL3, and CCL4, in women who ultimately underwent sPTL or PPROM. The primary receptor for CCL2 is CCR2, which is predominantly expressed by inflammatory monocytes and controls the trafficking of such cells (Griffith et al., 2014). CCL2 is rapidly produced by activated tissue or immune cells, and CCL2/CCR2 interactions are considered to be required for inflammatory monocyte migration into peripheral tissues (Kuziel et al., 1997). CCL3 and CCL4 can signal through CCR1 and CCR5, which can be expressed by monocytes and T cells (Griffith et al., 2014; Dyer, 2020). CCR1 and CCR5 have been demonstrated to promote monocyte adhesion and transmigration in an in vitro setting (Weber et al., 2001). Indeed, monocytes and macrophages are found in the lower reproductive tract in low numbers (Wang et al., 2021), including during pregnancy (Timmons et al., 2009), and their abundance is associated with inflammation (Wang et al., 2021). In addition, the priming of CD8+ T cells also relies on CCL3/CCL4 signaling through CCR5 (Castellino et al., 2006; Hugues et al., 2007), thus the increased presence of these chemokines in the vaginal fluid of women who experience sPTB has interesting implications for the pathogenesis of preterm birth. In the context of prior findings, our results suggest that increased chemokine concentrations may contribute to a hostile vaginal milieu through enhanced infiltration of monocytes that could then activate local T cells, a considerable portion of the vaginal immune cell composition (Lee et al., 2015). Our findings are in line with a prior report that demonstrated increased cervico-vaginal concentrations of CCL2 in women who underwent preterm birth compared to those who delivered at term (Fettweis et al., 2019). Moreover, women who ultimately will develop a short cervix, which is a strong predictor of sPTB (Andersen et al., 1990; Iams et al., 1996; Heath et al., 1998; Hassan et al., 2000; Goldenberg et al., 2008; Romero et al., 2014a), displayed a fivefold increase in their vaginal concentrations of CCL2 compared to controls (Chandiramani et al., 2012). These data suggest that women destined to undergo sPTL and PPROM share a common signature of monocyte recruitment prior to disease onset; indeed, such infiltrating cells may represent a source of the acute vaginal cytokine response (i.e., elevated concentrations of IL-6 and IL-1β) that was also observed herein. However, the evaluation of individual mediator kinetics throughout pregnancy would require a substantially greater number of sampling points, making the determination of whether chemokine release precedes the acute inflammatory response nearly impossible. Nonetheless, the role of such mediators in the pathogenesis of each subset of sPTB requires further investigation.

AMPs, which include defensins, cathelicidins, whey acidic proteins, lysozymes, C-type lectins, and S100 proteins, among others, are soluble mediators that participate in the host innate immune response against pathogens in the FRT (Yarbrough et al., 2015). Defensins are the largest family of AMPs found in humans, comprising small cationic peptides produced by a variety of immune and nonimmune cells, and are subdivided into α, β, and θ defensins (Lichtenstein, 1991; Yang et al., 2002; Maisetta et al., 2003; Ganz, 2003). Specifically, there are four human β-defensins (HBD-1–4) which are primarily expressed by epithelial cells and have been reported in the FRT (King et al., 2003; Yarbrough et al., 2015), including the vaginal fluid (Elovitz et al., 2019; Florova et al., 2021) as well as in the gestational tissues (Espinoza et al., 2003; Soto et al., 2007; King et al., 2007; Kim et al., 2022). Indeed, the vaginal concentrations of β-defensin-2 were found to be decreased in women who ultimately underwent sPTB compared to those who delivered at term (Elovitz et al., 2019). Consistently, in the current study we confirmed that the vaginal concentrations of β-defensin-2 are decreased in women with sPTB, particularly in those with early PPROM. Early PPROM has been previously associated with increased rates of neonatal morbidity (Goya et al., 2013; Yu et al., 2015; Pinto et al., 2019) and mortality (Goya et al., 2013; González-Mesa et al., 2021; Yu et al., 2015), thus women at risk for this subset of sPTB represent a target population for the development of predictive and preventive clinical tools. Such a decrease in β-defensin-2 was mirrored by SLPI, another AMP that has also been reported in the FRT and vaginal fluid (Yarbrough et al., 2015; Florova et al., 2021). SLPI is a secreted inhibitor that protects host cells against damage from extracellular proteases and is a central player in the constitutive host response in the FRT (Hein et al., 2002; Itaoka et al., 2015; Florova et al., 2021). We previously showed that SLPI is negatively correlated with Gemella spp. (Florova et al., 2021), a member of the vaginal community state type (CST) IV (Ravel et al., 2011) that is linked to increased risk for preterm birth (DiGiulio et al., 2015; Tabatabaei et al., 2019; Elovitz et al., 2019; Hočevar et al., 2019; Chang et al., 2020; Odogwu et al., 2021; Kumar et al., 2021; Dunlop et al., 2021). Similar to SLPI, reduced vaginal concentrations of β-defensin-2 are associated with vaginal CST IV and sPTB (Elovitz et al., 2019). Taken together, these results suggest that the vaginal ecosystem of women who are destined to undergo early PPROM displays a suppressed AMP-driven host response; however, additional research is required to determine whether this decrease reflects an impaired or a dampened response.

A distinct finding is that VEGF, uniquely among the growth factors, was decreased in women who experienced sPTB. VEGF is one member of a family of pro-angiogenic, pro-vasculogenic growth factors with mild immunobiological functions including hematopoiesis (Gerber and Ferrara, 2003; Gerber et al., 2002) and vascular permeability (Chen et al., 2012; Lal et al., 2001). Indeed, disruption of VEGF proteins and their receptors is largely implicated in diseases associated with vascular malformations including obstetrical diseases such as preeclampsia (Tarca et al., 2019; Tarca et al., 2022; Chaiworapongsa et al., 2004), a known etiology of iatrogenic preterm birth (Goldenberg et al., 2008). Interestingly, while disrupted vascularization is an accepted risk factor of sPTB (Visser et al., 2021), the evidence surrounding VEGF’s role remains limited. While one study implicated decreased amniotic fluid levels of VEGF in PPROM (Savasan et al., 2010), another study found no association between preterm birth and VEGF in the cervico-vaginal space (Yilmaz et al., 2014). Yet, more recently, we showed that vaginal concentrations of VEGF were negatively correlated with Gemella spp. in women who went on to experience preterm birth (Florova et al., 2021). In the context of previous studies, our data suggest that a hostile vaginal milieu may lead to reduced VEGF levels and functions, such as angiogenesis, which could be implicated with early preterm birth regardless of the process of membrane rupture.

A major finding of the current study is that the vaginal immunoproteome sampled prior to 24 weeks of gestation can be utilized to generate noninvasive biomarkers with potential utility for the prediction of sPTB occurring before 30 weeks of gestation. This window of sampling is clinically relevant, given that ultrasound screening is performed between 20 and 24 weeks of gestation and improves the feasibility of implementing vaginal sampling for cytokine determinations as part of prenatal care. Another advantage of our model is its potential for the prediction of early sPTB, which is associated with more severe neonatal outcomes than those cases occurring after 34 weeks of gestation (Callaghan et al., 2006; Crump et al., 2019) and may provide the opportunity for personalized patient management to improve adverse perinatal outcomes. It is worth mentioning that the models generated herein showed the best predictive value for early PPROM, which highlights the importance of distinguishing between different subsets of sPTB (i.e., early and late sPTL and PPROM) to improve prediction. Indeed, for pregnancies resulting in early preterm birth, the immunoproteome provides improved predictive strength over previous biomarker models that utilized the vaginal microbiome (Romero et al., 2022). Nonetheless, our results as well as those of previous studies suggest that the assessment of the immune response and its interactions with the microbiome (Fettweis et al., 2019; Flaviani et al., 2021; Florova et al., 2021; Elovitz et al., 2019) could be considered together with other prenatal screening tools to construct a comprehensive minimally invasive screening tool for preterm birth.

Herein, we also showed that overall maternal characteristics alone have a poor predictability for all subsets of preterm birth; yet, the combination of the vaginal immunoproteome and maternal characteristics improved such predictive capacity. Furthermore, while the predictability of the vaginal immunoproteome alone was not superior to that of the sonographic cervical length, the combination of the vaginal immunoproteome and cervical length improved the predictive value for early PPROM. This is important because there is an imperative need for finding noninvasive biomarkers to predict preterm birth in low-resource areas wherein there is a high risk for this pregnancy complication (DeFranco et al., 2008; Smith et al., 2007). Although sonographic cervical length remains an excellent predictor for preterm birth, the implementation of cervical length measurement as a universal screening modality for sPTB worldwide has been challenging. Indeed, even developed countries have not been able to enact widespread universal screening of cervical length due to logistic barriers as well as patient refusal to participate in this intrusive procedure (Temming et al., 2016; Pedretti et al., 2017). From a logistical standpoint, the accurate acquisition and interpretation of cervical length measurements require a highly trained maternal-fetal specialist (Iams et al., 2013). As of 2018, only 1570 maternal-fetal medicine specialists were registered in the US workforce (Wenstrom et al., 2018) and these specialists are neither distributed equally across the country nor the world, thereby representing a scarce resource. Also, the ultrasound equipment and facilities required to perform cervical length examinations have a prohibitive cost and are unavailable to many women, especially those who are medically underserved, reflecting widespread disparities in medicine (Haviland et al., 2016). Furthermore, only 1–2% of pregnant mothers have the clinical finding of a sonographic short cervix in a mid-trimester transvaginal ultrasound screening (Fonseca et al., 2007). Among these women, selective administration of vaginal progesterone will reduce the risk of delivery before 37 weeks by half (Fonseca et al., 2007). Thus, while this pairing of predictive and preventive tools to sPTB has been modestly effective, the population of pregnant women for whom both cervical length and progesterone administration are beneficial represents a small fraction of the 10% of women who deliver preterm worldwide (Chawanpaiboon et al., 2019; Martin and Hamilton, 2021). Therefore, investigating biomarkers, including previously suggested immune mediators (e.g. SLPI; Florova et al., 2021) and β-defensin-2 (Elovitz et al., 2019), that can be easily collected and analyzed in a scalable manner could overcome these shortcomings. As shown here, the addition of the vaginal immunoproteome improved the predictability for specific subsets of preterm birth, specifically early PPROM. An advantage of vaginal sampling is that self-swabbing is now considered an effective way of vaginal fluid collection (Haguenoer et al., 2014; Lunny et al., 2015); therefore, a screening tool based on vaginal biomarkers may be developed for use in low-resource areas with a scarcity of healthcare providers. Herein, vaginal immune mediators were identified with distinct patterns between women who delivered at term and those who delivered preterm. Collectively, the identified vaginal immune mediators in this study could potentially be incorporated into a comprehensive molecular screening assay capable of supplementing sonographic short cervix screening, and even supplanting it in low-resource areas. Yet, further research is needed to investigate its utility.

A limitation of the current report is that, despite our comprehensive survey of the vaginal immunoproteome, the identification of causal mechanisms driving the changes in specific mediators associated with different subsets of preterm birth is yet to be elucidated. The incorporation of microbiome and other omics, as well as mechanistic approaches requiring the utilization of animal models, was outside the scope of the research question investigated herein. Yet, we consider that the substantial data generated in this study, together with our predictive models, can serve to spark new investigations focused on targeting key mediators and their relationships with local immune-microbiome interactions in the context of pregnancy complications. Lastly, the population included in this study was primarily composed of African-American women. Additional studies are required to ascertain the generalizability of these results to other populations.

The current study represents the largest longitudinal survey of the vaginal immunoproteome in a population at high risk for sPTB. We report that, throughout uncomplicated gestation, the vaginal immunoproteome harbors a cytokine network that represents a homeostatic profile similar to that observed in other body sites during the second phase of pregnancy. By contrast, the vaginal immunoproteome is skewed toward a pro-inflammatory state in women who ultimately undergo sPTL and PPROM. Such an inflammatory profile includes increased monocyte chemoattractants, cytokines associated with macrophage and T-cell activation, and the consistent reduction of antimicrobial proteins/peptides. Notably, our data show that the vaginal immunoproteome during the second trimester holds predictive value for PPROM before 30 weeks of gestation, indicating that the vaginal immune response can be leveraged as part of a noninvasive approach for the prediction of early sPTB, the leading cause of neonatal morbidity and mortality worldwide.

The data generated during this study are available on GitHub (copy archived at Tarca, 2024).

1. 1. Aghaeepour N
   2. Ganio EA
   3. Mcilwain D
   4. Tsai AS
   5. Tingle M
   6. Van Gassen S
   7. Gaudilliere DK
   8. Baca Q
   9. McNeil L
   10. Okada R
   11. Ghaemi MS
   12. Furman D
   13. Wong RJ
   14. Winn VD
   15. Druzin ML
   16. El-Sayed YY
   17. Quaintance C
   18. Gibbs R
   19. Darmstadt GL
   20. Shaw GM
   21. Stevenson DK
   22. Tibshirani R
   23. Nolan GP
   24. Lewis DB
   25. Angst MS
   26. Gaudilliere B

   (2017) An immune clock of human pregnancy

   Science Immunology 2:eaan2946.

   https://doi.org/10.1126/sciimmunol.aan2946

   • PubMed
   • Google Scholar
2. 1. Aghaeepour N
   2. Lehallier B
   3. Baca Q
   4. Ganio EA
   5. Wong RJ
   6. Ghaemi MS
   7. Culos A
   8. El-Sayed YY
   9. Blumenfeld YJ
   10. Druzin ML
   11. Winn VD
   12. Gibbs RS
   13. Tibshirani R
   14. Shaw GM
   15. Stevenson DK
   16. Gaudilliere B
   17. Angst MS

   (2018) A proteomic clock of human pregnancy

   American Journal of Obstetrics and Gynecology 218:347.

   https://doi.org/10.1016/j.ajog.2017.12.208

   • PubMed
   • Google Scholar
3. 1. Amabebe E
   2. Chapman DR
   3. Stern VL
   4. Stafford G
   5. Anumba DOC

   (2018) Mid-gestational changes in cervicovaginal fluid cytokine levels in asymptomatic pregnant women are predictive markers of inflammation-associated spontaneous preterm birth

   Journal of Reproductive Immunology 126:1–10.

   https://doi.org/10.1016/j.jri.2018.01.001

   • PubMed
   • Google Scholar
4. 1. American College of Obstetricians and Gynecologists

   (2016) Practice bulletin no. 171: management of preterm labor

   Obstetrics & Gynecology 128:e155–e164.

   https://doi.org/10.1097/AOG.0000000000001711

   • Google Scholar
5. 1. American College of Obstetricians and Gynecologists

   (2021) Prediction and prevention of spontaneous preterm birth

   Obstetrics & Gynecology 138:e65–e90.

   https://doi.org/10.1097/AOG.0000000000004479

   • Google Scholar
6. 1. Andersen HF
   2. Nugent CE
   3. Wanty SD
   4. Hayashi RH

   (1990) Prediction of risk for preterm delivery by ultrasonographic measurement of cervical length

   American Journal of Obstetrics and Gynecology 163:859–867.

   https://doi.org/10.1016/0002-9378(90)91084-p

   • PubMed
   • Google Scholar
7. 1. Apte RS
   2. Chen DS
   3. Ferrara N

   (2019) VEGF in signaling and disease: beyond discovery and development

   Cell 176:1248–1264.

   https://doi.org/10.1016/j.cell.2019.01.021

   • PubMed
   • Google Scholar
8. 1. Ashford KB
   2. Chavan N
   3. Ebersole JL
   4. Wiggins AT
   5. Sharma S
   6. McCubbin A
   7. Barnett J
   8. O’Brien J

   (2018) Patterns of systemic and cervicovaginal fluid inflammatory cytokines throughout pregnancy

   American Journal of Perinatology 35:455–462.

   https://doi.org/10.1055/s-0037-1608677

   • PubMed
   • Google Scholar
9. 1. Athayde N
   2. Romero R
   3. Maymon E
   4. Gomez R
   5. Pacora P
   6. Yoon BH
   7. Edwin SS

   (2000) Interleukin 16 in pregnancy, parturition, rupture of fetal membranes, and microbial invasion of the amniotic cavity

   American Journal of Obstetrics and Gynecology 182:135–141.

   https://doi.org/10.1016/s0002-9378(00)70502-3

   • PubMed
   • Google Scholar
10. 1. Baggia S
    2. Gravett MG
    3. Witkin SS
    4. Haluska GJ
    5. Novy MJ

    (1996) Interleukin-1 beta intra-amniotic infusion induces tumor necrosis factor-alpha, prostaglandin production, and preterm contractions in pregnant rhesus monkeys

    Journal of the Society for Gynecologic Investigation 3:121–126.

    https://doi.org/10.1177/107155769600300304

    • PubMed
    • Google Scholar
11. 1. Barata JT
    2. Durum SK
    3. Seddon B

    (2019) Flip the coin: IL-7 and IL-7R in health and disease

    Nature Immunology 20:1584–1593.

    https://doi.org/10.1038/s41590-019-0479-x

    • PubMed
    • Google Scholar
12. 1. Bates D
    2. Machler M

    (2015) Fitting linear mixed-effects models using lme4

    Journal of Statistical Software 67:1–48.

    https://doi.org/10.18637/jss.v067.i01

    • Google Scholar
13. 1. Becher B
    2. Tugues S
    3. Greter M

    (2016) GM-CSF: from growth factor to central mediator of tissue inflammation

    Immunity 45:963–973.

    https://doi.org/10.1016/j.immuni.2016.10.026

    • PubMed
    • Google Scholar
14. 1. Benjelloun F
    2. Quillay H
    3. Cannou C
    4. Marlin R
    5. Madec Y
    6. Fernandez H
    7. Chrétien F
    8. Le Grand R
    9. Barré-Sinoussi F
    10. Nugeyre MT
    11. Menu E

    (2020) Activation of toll-like receptors differentially modulates inflammation in the human reproductive tract: preliminary findings

    Frontiers in Immunology 11:1655.

    https://doi.org/10.3389/fimmu.2020.01655

    • PubMed
    • Google Scholar
15. 1. Bennett SL
    2. Cullen JB
    3. Sherer DM
    4. Woods JR

    (1993) The ferning and nitrazine tests of amniotic fluid between 12 and 41 weeks gestation

    American Journal of Perinatology 10:101–104.

    https://doi.org/10.1055/s-2007-994637

    • PubMed
    • Google Scholar
16. 1. Blencowe H
    2. Lee ACC
    3. Cousens S
    4. Bahalim A
    5. Narwal R
    6. Zhong N
    7. Chou D
    8. Say L
    9. Modi N
    10. Katz J
    11. Vos T
    12. Marlow N
    13. Lawn JE

    (2013) Preterm birth-associated neurodevelopmental impairment estimates at regional and global levels for 2010

    Pediatric Research 74 Suppl 1:17–34.

    https://doi.org/10.1038/pr.2013.204

    • PubMed
    • Google Scholar
17. 1. Breiman L

    (2001) Random forests

    Machine Learning 45:5–32.

    https://doi.org/10.1023/A:1010933404324

    • Google Scholar
18. 1. Cahill CM
    2. Rogers JT

    (2008) Interleukin (IL) 1beta induction of IL-6 is mediated by a novel phosphatidylinositol 3-kinase-dependent AKT/IkappaB kinase alpha pathway targeting activator protein-1

    The Journal of Biological Chemistry 283:25900–25912.

    https://doi.org/10.1074/jbc.M707692200

    • PubMed
    • Google Scholar
19. 1. Callaghan WM
    2. MacDorman MF
    3. Rasmussen SA
    4. Qin C
    5. Lackritz EM

    (2006) The contribution of preterm birth to infant mortality rates in the United States

    Pediatrics 118:1566–1573.

    https://doi.org/10.1542/peds.2006-0860

    • PubMed
    • Google Scholar
20. 1. Camunas-Soler J
    2. Gee EPS
    3. Reddy M
    4. Mi JD
    5. Thao M
    6. Brundage T
    7. Siddiqui F
    8. Hezelgrave NL
    9. Shennan AH
    10. Namsaraev E
    11. Haverty C
    12. Jain M
    13. Elovitz MA
    14. Rasmussen M
    15. Tribe RM

    (2022) Predictive RNA profiles for early and very early spontaneous preterm birth

    American Journal of Obstetrics and Gynecology 227:72.

    https://doi.org/10.1016/j.ajog.2022.04.002

    • PubMed
    • Google Scholar
21. 1. Capece A
    2. Vasieva O
    3. Meher S
    4. Alfirevic Z
    5. Alfirevic A

    (2014) Pathway analysis of genetic factors associated with spontaneous preterm birth and pre-labor preterm rupture of membranes

    PLOS ONE 9:e108578.

    https://doi.org/10.1371/journal.pone.0108578

    • PubMed
    • Google Scholar
22. 1. Castellino F
    2. Huang AY
    3. Altan-Bonnet G
    4. Stoll S
    5. Scheinecker C
    6. Germain RN

    (2006) Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T cell-dendritic cell interaction

    Nature 440:890–895.

    https://doi.org/10.1038/nature04651

    • PubMed
    • Google Scholar
23. 1. Chaiworapongsa T
    2. Romero R
    3. Espinoza J
    4. Bujold E
    5. Mee Kim Y
    6. Gonçalves LF
    7. Gomez R
    8. Edwin S

    (2004) Evidence supporting a role for blockade of the vascular endothelial growth factor system in the pathophysiology of preeclampsia: young investigator award

    American Journal of Obstetrics and Gynecology 190:1541–1547.

    https://doi.org/10.1016/j.ajog.2004.03.043

    • PubMed
    • Google Scholar
24. 1. Chan D
    2. Bennett PR
    3. Lee YS
    4. Kundu S
    5. Teoh TG
    6. Adan M
    7. Ahmed S
    8. Brown RG
    9. David AL
    10. Lewis HV
    11. Gimeno-Molina B
    12. Norman JE
    13. Stock SJ
    14. Terzidou V
    15. Kropf P
    16. Botto M
    17. MacIntyre DA
    18. Sykes L

    (2022) Microbial-driven preterm labour involves crosstalk between the innate and adaptive immune response

    Nature Communications 13:975.

    https://doi.org/10.1038/s41467-022-28620-1

    • PubMed
    • Google Scholar
25. 1. Chandiramani M
    2. Seed PT
    3. Orsi NM
    4. Ekbote UV
    5. Bennett PR
    6. Shennan AH
    7. Tribe RM

    (2012) Limited relationship between cervico-vaginal fluid cytokine profiles and cervical shortening in women at high risk of spontaneous preterm birth

    PLOS ONE 7:e52412.

    https://doi.org/10.1371/journal.pone.0052412

    • PubMed
    • Google Scholar
26. 1. Chang D-H
    2. Shin J
    3. Rhee M-S
    4. Park K-R
    5. Cho B-K
    6. Lee S-K
    7. Kim B-C

    (2020) Vaginal microbiota profiles of native korean women and associations with high-risk pregnancy

    Journal of Microbiology and Biotechnology 30:248–258.

    https://doi.org/10.4014/jmb.1908.08016

    • Google Scholar
27. 1. Chawanpaiboon S
    2. Vogel JP
    3. Moller AB
    4. Lumbiganon P
    5. Petzold M
    6. Hogan D
    7. Landoulsi S
    8. Jampathong N
    9. Kongwattanakul K
    10. Laopaiboon M
    11. Lewis C
    12. Rattanakanokchai S
    13. Teng DN
    14. Thinkhamrop J
    15. Watananirun K
    16. Zhang J
    17. Zhou W
    18. Gülmezoglu AM

    (2019) Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis

    The Lancet. Global Health 7:e37–e46.

    https://doi.org/10.1016/S2214-109X(18)30451-0

    • PubMed
    • Google Scholar
28. 1. Chen XL
    2. Nam JO
    3. Jean C
    4. Lawson C
    5. Walsh CT
    6. Goka E
    7. Lim ST
    8. Tomar A
    9. Tancioni I
    10. Uryu S
    11. Guan JL
    12. Acevedo LM
    13. Weis SM
    14. Cheresh DA
    15. Schlaepfer DD

    (2012) VEGF-induced vascular permeability is mediated by FAK

    Developmental Cell 22:146–157.

    https://doi.org/10.1016/j.devcel.2011.11.002

    • PubMed
    • Google Scholar
29. 1. Chupp GL
    2. Wright EA
    3. Wu D
    4. Vallen-Mashikian M
    5. Cruikshank WW
    6. Center DM
    7. Kornfeld H
    8. Berman JS

    (1998) Tissue and T cell distribution of precursor and mature IL-16

    Journal of Immunology 161:3114–3119.

    https://doi.org/10.4049/jimmunol.161.6.3114

    • PubMed
    • Google Scholar
30. 1. Cole AM

    (2006)

    Innate host defense of human vaginal and cervical mucosae

    Current Topics in Microbiology and Immunology 306:199–230.

    • PubMed
    • Google Scholar
31. 1. Cole AM
    2. Cole AL

    (2008) Antimicrobial polypeptides are key anti-HIV-1 effector molecules of cervicovaginal host defense

    American Journal of Reproductive Immunology 59:27–34.

    https://doi.org/10.1111/j.1600-0897.2007.00561.x

    • PubMed
    • Google Scholar
32. 1. Conde-Agudelo A
    2. Romero R
    3. Da Fonseca E
    4. O’Brien JM
    5. Cetingoz E
    6. Creasy GW
    7. Hassan SS
    8. Erez O
    9. Pacora P
    10. Nicolaides KH

    (2018) Vaginal progesterone is as effective as cervical cerclage to prevent preterm birth in women with a singleton gestation, previous spontaneous preterm birth, and a short cervix: updated indirect comparison meta-analysis

    American Journal of Obstetrics and Gynecology 219:10–25.

    https://doi.org/10.1016/j.ajog.2018.03.028

    • PubMed
    • Google Scholar
33. 1. Crump C
    2. Sundquist J
    3. Winkleby MA
    4. Sundquist K

    (2019) Gestational age at birth and mortality from infancy into mid-adulthood: a national cohort study

    The Lancet. Child & Adolescent Health 3:408–417.

    https://doi.org/10.1016/S2352-4642(19)30108-7

    • PubMed
    • Google Scholar
34. 1. DeFranco EA
    2. Lian M
    3. Muglia LA
    4. Schootman M

    (2008) Area-level poverty and preterm birth risk: a population-based multilevel analysis

    BMC Public Health 8:316.

    https://doi.org/10.1186/1471-2458-8-316

    • PubMed
    • Google Scholar
35. 1. Delgado-Diaz DJ
    2. Jesaveluk B
    3. Hayward JA
    4. Tyssen D
    5. Alisoltani A
    6. Potgieter M
    7. Bell L
    8. Ross E
    9. Iranzadeh A
    10. Allali I
    11. Dabee S
    12. Barnabas S
    13. Gamieldien H
    14. Blackburn JM
    15. Mulder N
    16. Smith SB
    17. Edwards VL
    18. Burgener AD
    19. Bekker L-G
    20. Ravel J
    21. Passmore J-AS
    22. Masson L
    23. Hearps AC
    24. Tachedjian G

    (2022) Lactic acid from vaginal microbiota enhances cervicovaginal epithelial barrier integrity by promoting tight junction protein expression

    Microbiome 10:141.

    https://doi.org/10.1186/s40168-022-01337-5

    • PubMed
    • Google Scholar
36. 1. DiGiulio DB
    2. Callahan BJ
    3. McMurdie PJ
    4. Costello EK
    5. Lyell DJ
    6. Robaczewska A
    7. Sun CL
    8. Goltsman DSA
    9. Wong RJ
    10. Shaw G
    11. Stevenson DK
    12. Holmes SP
    13. Relman DA

    (2015) Temporal and spatial variation of the human microbiota during pregnancy

    PNAS 112:11060–11065.

    https://doi.org/10.1073/pnas.1502875112

    • PubMed
    • Google Scholar
37. 1. Di Paola M
    2. Seravalli V
    3. Paccosi S
    4. Linari C
    5. Parenti A
    6. De Filippo C
    7. Tanturli M
    8. Vitali F
    9. Torcia MG
    10. Di Tommaso M

    (2020) Identification of vaginal microbial communities associated with extreme cervical shortening in pregnant women

    Journal of Clinical Medicine 9:3621.

    https://doi.org/10.3390/jcm9113621

    • PubMed
    • Google Scholar
38. 1. Donders GGG
    2. Vereecken A
    3. Bosmans E
    4. Spitz B

    (2003) Vaginal cytokines in normal pregnancy

    American Journal of Obstetrics and Gynecology 189:1433–1438.

    https://doi.org/10.1067/S0002-9378(03)00653-7

    • Google Scholar
39. 1. Donders G
    2. Van Calsteren K
    3. Bellen G
    4. Reybrouck R
    5. Van den Bosch T
    6. Riphagen I
    7. Van Lierde S

    (2009) Predictive value for preterm birth of abnormal vaginal flora, bacterial vaginosis and aerobic vaginitis during the first trimester of pregnancy

    BJOG 116:1315–1324.

    https://doi.org/10.1111/j.1471-0528.2009.02237.x

    • Google Scholar
40. 1. Dunlop AL
    2. Satten GA
    3. Hu Y-J
    4. Knight AK
    5. Hill CC
    6. Wright ML
    7. Smith AK
    8. Read TD
    9. Pearce BD
    10. Corwin EJ

    (2021) Vaginal microbiome composition in early pregnancy and risk of spontaneous preterm and early term birth among african american women

    Frontiers in Cellular and Infection Microbiology 11:641005.

    https://doi.org/10.3389/fcimb.2021.641005

    • Google Scholar
41. 1. Dutta EH
    2. Behnia F
    3. Boldogh I
    4. Saade GR
    5. Taylor BD
    6. Kacerovský M
    7. Menon R

    (2016) Oxidative stress damage-associated molecular signaling pathways differentiate spontaneous preterm birth and preterm premature rupture of the membranes

    Molecular Human Reproduction 22:143–157.

    https://doi.org/10.1093/molehr/gav074

    • Google Scholar
42. 1. Dvorakova L
    2. Ivankova K
    3. Krofta L
    4. Hromadnikova I

    (2017) Expression profile of heat shock proteins in placental tissues of patients with preterm prelabor rupture of membranes and spontaneous preterm labor with intact membranes

    American Journal of Reproductive Immunology 78:2698.

    https://doi.org/10.1111/aji.12698

    • PubMed
    • Google Scholar
43. 1. Dvorakova L
    2. Ivankova K

    (2020) Prelabor rupture of membranes

    Obstetrics & Gynecology 135:e80–e97.

    https://doi.org/10.1097/AOG.0000000000003700

    • Google Scholar
44. 1. Dyer DP

    (2020) Understanding the mechanisms that facilitate specificity, not redundancy, of chemokine-mediated leukocyte recruitment

    Immunology 160:336–344.

    https://doi.org/10.1111/imm.13200

    • PubMed
    • Google Scholar
45. 1. Elovitz MA
    2. Gajer P
    3. Riis V
    4. Brown AG
    5. Humphrys MS
    6. Holm JB
    7. Ravel J

    (2019) Cervicovaginal microbiota and local immune response modulate the risk of spontaneous preterm delivery

    Nature Communications 10:1305.

    https://doi.org/10.1038/s41467-019-09285-9

    • PubMed
    • Google Scholar
46. 1. Ely DM
    2. Driscoll AK

    (2020)

    Infant mortality in the united states, 2018: data from the period linked birth/infant death file

    National Vital Statistics Reports 69:1–18.

    • PubMed
    • Google Scholar
47. 1. Erez O
    2. Romero R
    3. Tarca AL
    4. Chaiworapongsa T
    5. Kim YM
    6. Than NG
    7. Vaisbuch E
    8. Draghici S
    9. Tromp G

    (2009) Differential expression pattern of genes encoding for anti-microbial peptides in the fetal membranes of patients with spontaneous preterm labor and intact membranes and those with preterm prelabor rupture of the membranes

    The Journal of Maternal-Fetal & Neonatal Medicine 22:1103–1115.

    https://doi.org/10.3109/14767050902994796

    • PubMed
    • Google Scholar
48. 1. Erlebacher A

    (2013) Immunology of the maternal-fetal interface

    Annual Review of Immunology 31:387–411.

    https://doi.org/10.1146/annurev-immunol-032712-100003

    • PubMed
    • Google Scholar
49. 1. Espinoza J
    2. Chaiworapongsa T
    3. Romero R
    4. Edwin S
    5. Rathnasabapathy C
    6. Gomez R
    7. Bujold E
    8. Camacho N
    9. Kim YM
    10. Hassan S
    11. Blackwell S
    12. Whitty J
    13. Berman S
    14. Redman M
    15. Yoon BH
    16. Sorokin Y

    (2003) Antimicrobial peptides in amniotic fluid: defensins, calprotectin and bacterial/permeability-increasing protein in patients with microbial invasion of the amniotic cavity, intra-amniotic inflammation, preterm labor and premature rupture of membranes

    The Journal of Maternal-Fetal & Neonatal Medicine 13:2–21.

    https://doi.org/10.1080/jmf.13.1.2.21

    • Google Scholar
50. 1. Ethuin F
    2. Delarche C
    3. Gougerot-Pocidalo MA
    4. Eurin B
    5. Jacob L
    6. Chollet-Martin S

    (2003) Regulation of interleukin 12 p40 and p70 production by blood and alveolar phagocytes during severe sepsis

    Laboratory Investigation; a Journal of Technical Methods and Pathology 83:1353–1360.

    https://doi.org/10.1097/01.lab.0000087589.37269.fc

    • PubMed
    • Google Scholar
51. 1. Farias-Jofre M
    2. Romero R
    3. Galaz J
    4. Xu Y
    5. Miller D
    6. Garcia-Flores V
    7. Arenas-Hernandez M
    8. Winters AD
    9. Berkowitz BA
    10. Podolsky RH
    11. Shen Y
    12. Kanninen T
    13. Panaitescu B
    14. Glazier CR
    15. Pique-Regi R
    16. Theis KR
    17. Gomez-Lopez N

    (2023) Blockade of IL-6R prevents preterm birth and adverse neonatal outcomes

    EBioMedicine 98:104865.

    https://doi.org/10.1016/j.ebiom.2023.104865

    • PubMed
    • Google Scholar
52. 1. Faro J
    2. Romero R
    3. Schwenkel G
    4. Garcia-Flores V
    5. Arenas-Hernandez M
    6. Leng Y
    7. Xu Y
    8. Miller D
    9. Hassan SS
    10. Gomez-Lopez N

    (2019) Intra-amniotic inflammation induces preterm birth by activating the NLRP3 inflammasome†

    Biology of Reproduction 100:1290–1305.

    https://doi.org/10.1093/biolre/ioy261

    • PubMed
    • Google Scholar
53. 1. Fehniger TA
    2. Caligiuri MA

    (2001) Interleukin 15: biology and relevance to human disease

    Blood 97:14–32.

    https://doi.org/10.1182/blood.v97.1.14

    • PubMed
    • Google Scholar
54. 1. Ferrara N
    2. Gerber H-P
    3. LeCouter J

    (2003) The biology of VEGF and its receptors

    Nature Medicine 9:669–676.

    https://doi.org/10.1038/nm0603-669

    • PubMed
    • Google Scholar
55. 1. Fettweis JM
    2. Serrano MG
    3. Brooks JP
    4. Edwards DJ
    5. Girerd PH
    6. Parikh HI
    7. Huang B
    8. Arodz TJ
    9. Edupuganti L
    10. Glascock AL
    11. Xu J
    12. Jimenez NR
    13. Vivadelli SC
    14. Fong SS
    15. Sheth NU
    16. Jean S
    17. Lee V
    18. Bokhari YA
    19. Lara AM
    20. Mistry SD
    21. Duckworth RA
    22. Bradley SP
    23. Koparde VN
    24. Orenda XV
    25. Milton SH
    26. Rozycki SK
    27. Matveyev AV
    28. Wright ML
    29. Huzurbazar SV
    30. Jackson EM
    31. Smirnova E
    32. Korlach J
    33. Tsai Y-C
    34. Dickinson MR
    35. Brooks JL
    36. Drake JI
    37. Chaffin DO
    38. Sexton AL
    39. Gravett MG
    40. Rubens CE
    41. Wijesooriya NR
    42. Hendricks-Muñoz KD
    43. Jefferson KK
    44. Strauss JF
    45. Buck GA

    (2019) The vaginal microbiome and preterm birth

    Nature Medicine 25:1012–1021.

    https://doi.org/10.1038/s41591-019-0450-2

    • PubMed
    • Google Scholar
56. 1. Flaviani F
    2. Hezelgrave NL
    3. Kanno T
    4. Prosdocimi EM
    5. Chin-Smith E
    6. Ridout AE
    7. von Maydell DK
    8. Mistry V
    9. Wade WG
    10. Shennan AH
    11. Dimitrakopoulou K
    12. Seed PT
    13. Mason AJ
    14. Tribe RM

    (2021) Cervicovaginal microbiota and metabolome predict preterm birth risk in an ethnically diverse cohort

    JCI Insight 6:e149257.

    https://doi.org/10.1172/jci.insight.149257

    • PubMed
    • Google Scholar
57. 1. Florova V
    2. Romero R
    3. Tarca AL
    4. Galaz J
    5. Motomura K
    6. Ahmad MM
    7. Hsu C-D
    8. Hsu R
    9. Tong A
    10. Ravel J
    11. Theis KR
    12. Gomez-Lopez N

    (2021) Vaginal host immune-microbiome interactions in a cohort of primarily African-American women who ultimately underwent spontaneous preterm birth or delivered at term

    Cytokine 137:155316.

    https://doi.org/10.1016/j.cyto.2020.155316

    • PubMed
    • Google Scholar
58. 1. Fonseca EB
    2. Celik E
    3. Parra M
    4. Singh M
    5. Nicolaides KH

    (2007) Progesterone and the risk of preterm birth among women with a short cervix

    New England Journal of Medicine 357:462–469.

    https://doi.org/10.1056/NEJMoa067815

    • Google Scholar
59. 1. Fortunato SJ
    2. Menon R
    3. Lombardi SJ

    (1999) MMP/TIMP imbalance in amniotic fluid during PROM: an indirect support for endogenous pathway to membrane rupture

    Journal of Perinatal Medicine 27:362–368.

    https://doi.org/10.1515/JPM.1999.049

    • PubMed
    • Google Scholar
60. 1. Freitas AC
    2. Bocking A
    3. Hill JE
    4. Money DM

    (2018) Increased richness and diversity of the vaginal microbiota and spontaneous preterm birth

    Microbiome 6:117.

    https://doi.org/10.1186/s40168-018-0502-8

    • PubMed
    • Google Scholar
61. 1. Frey HA
    2. Stout MJ
    3. Pearson LN
    4. Tuuli MG
    5. Cahill AG
    6. Strauss JF
    7. Gomez LM
    8. Parry S
    9. Allsworth JE
    10. Macones GA

    (2016) Genetic variation associated with preterm birth in African-American women

    American Journal of Obstetrics and Gynecology 215:235.

    https://doi.org/10.1016/j.ajog.2016.03.008

    • PubMed
    • Google Scholar
62. 1. Friedman ML
    2. McElin TW

    (1969) Diagnosis of ruptured fetal membranes: clinical study and review of the literature

    American Journal of Obstetrics and Gynecology 104:544–550.

    https://doi.org/10.1016/s0002-9378(16)34244-2

    • PubMed
    • Google Scholar
63. 1. Galaz J
    2. Romero R
    3. Slutsky R
    4. Xu Y
    5. Motomura K
    6. Para R
    7. Pacora P
    8. Panaitescu B
    9. Hsu C-D
    10. Kacerovsky M
    11. Gomez-Lopez N

    (2020) Cellular immune responses in amniotic fluid of women with preterm prelabor rupture of membranes

    Journal of Perinatal Medicine 48:222–233.

    https://doi.org/10.1515/jpm-2019-0395

    • PubMed
    • Google Scholar
64. 1. Gandhi K
    2. Gutierrez P
    3. Garza J
    4. Gray Wlazlo TJ
    5. Meiser RJ
    6. David S
    7. Carrillo M
    8. Narasimhan M
    9. Galloway M
    10. Ventolini G

    (2020) Vaginal Lactobacillus species and inflammatory biomarkers in pregnancy

    Minerva Ginecologica 72:299–309.

    https://doi.org/10.23736/S0026-4784.20.04566-9

    • PubMed
    • Google Scholar
65. 1. Ganz T

    (2003) Defensins: antimicrobial peptides of innate immunity

    Nature Reviews Immunology 3:710–720.

    https://doi.org/10.1038/nri1180

    • Google Scholar
66. 1. Gerber H-P
    2. Malik AK
    3. Solar GP
    4. Sherman D
    5. Liang XH
    6. Meng G
    7. Hong K
    8. Marsters JC
    9. Ferrara N

    (2002) VEGF regulates haematopoietic stem cell survival by an internal autocrine loop mechanism

    Nature 417:954–958.

    https://doi.org/10.1038/nature00821

    • Google Scholar
67. 1. Gerber H-P
    2. Ferrara N

    (2003) The role of VEGF in normal and neoplastic hematopoiesis

    Journal of Molecular Medicine 81:20–31.

    https://doi.org/10.1007/s00109-002-0397-4

    • Google Scholar
68. 1. Gerson KD
    2. McCarthy C
    3. Elovitz MA
    4. Ravel J
    5. Sammel MD
    6. Burris HH

    (2020) Cervicovaginal microbial communities deficient in Lactobacillus species are associated with second trimester short cervix

    American Journal of Obstetrics and Gynecology 222:491.

    https://doi.org/10.1016/j.ajog.2019.11.1283

    • PubMed
    • Google Scholar
69. 1. Ghaemi MS
    2. DiGiulio DB
    3. Contrepois K
    4. Callahan B
    5. Ngo TTM
    6. Lee-McMullen B
    7. Lehallier B
    8. Robaczewska A
    9. Mcilwain D
    10. Rosenberg-Hasson Y
    11. Wong RJ
    12. Quaintance C
    13. Culos A
    14. Stanley N
    15. Tanada A
    16. Tsai A
    17. Gaudilliere D
    18. Ganio E
    19. Han X
    20. Ando K
    21. McNeil L
    22. Tingle M
    23. Wise P
    24. Maric I
    25. Sirota M
    26. Wyss-Coray T
    27. Winn VD
    28. Druzin ML
    29. Gibbs R
    30. Darmstadt GL
    31. Lewis DB
    32. Partovi Nia V
    33. Agard B
    34. Tibshirani R
    35. Nolan G
    36. Snyder MP
    37. Relman DA
    38. Quake SR
    39. Shaw GM
    40. Stevenson DK
    41. Angst MS
    42. Gaudilliere B
    43. Aghaeepour N

    (2019) Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy

    Bioinformatics 35:95–103.

    https://doi.org/10.1093/bioinformatics/bty537

    • PubMed
    • Google Scholar
70. 1. Goldenberg RL
    2. Hauth JC
    3. Andrews WW

    (2000) Intrauterine infection and preterm delivery

    New England Journal of Medicine 342:1500–1507.

    https://doi.org/10.1056/NEJM200005183422007

    • Google Scholar
71. 1. Goldenberg RL
    2. Culhane JF
    3. Iams JD
    4. Romero R

    (2008) Epidemiology and causes of preterm birth

    Lancet 371:75–84.

    https://doi.org/10.1016/S0140-6736(08)60074-4

    • PubMed
    • Google Scholar
72. 1. Gomez-Lopez N
    2. Guilbert LJ
    3. Olson DM

    (2010) Invasion of the leukocytes into the fetal-maternal interface during pregnancy

    Journal of Leukocyte Biology 88:625–633.

    https://doi.org/10.1189/jlb.1209796

    • PubMed
    • Google Scholar
73. 1. Gomez-Lopez N
    2. Romero R
    3. Xu Y
    4. Plazyo O
    5. Unkel R
    6. Leng Y
    7. Than NG
    8. Chaiworapongsa T
    9. Panaitescu B
    10. Dong Z
    11. Tarca AL
    12. Abrahams VM
    13. Yeo L
    14. Hassan SS

    (2017) A role for the inflammasome in spontaneous preterm labor with acute histologic chorioamnionitis

    Reproductive Sciences 24:1382–1401.

    https://doi.org/10.1177/1933719116687656

    • PubMed
    • Google Scholar
74. 1. Gomez-Lopez N
    2. Romero R
    3. Panaitescu B
    4. Leng Y
    5. Xu Y
    6. Tarca AL
    7. Faro J
    8. Pacora P
    9. Hassan SS
    10. Hsu CD

    (2018) Inflammasome activation during spontaneous preterm labor with intra-amniotic infection or sterile intra-amniotic inflammation

    American Journal of Reproductive Immunology 80:e13049.

    https://doi.org/10.1111/aji.13049

    • PubMed
    • Google Scholar
75. 1. Gomez-Lopez N
    2. Motomura K
    3. Miller D
    4. Garcia-Flores V
    5. Galaz J
    6. Romero R

    (2019a) Inflammasomes: their role in normal and complicated pregnancies

    The Journal of Immunology 203:2757–2769.

    https://doi.org/10.4049/jimmunol.1900901

    • Google Scholar
76. 1. Gomez-Lopez N
    2. Romero R
    3. Garcia-Flores V
    4. Leng Y
    5. Miller D
    6. Hassan SS
    7. Hsu C-D
    8. Panaitescu B

    (2019b) Inhibition of the NLRP3 inflammasome can prevent sterile intra-amniotic inflammation, preterm labor/birth, and adverse neonatal outcomes†

    Biology of Reproduction 100:1306–1318.

    https://doi.org/10.1093/biolre/ioy264

    • PubMed
    • Google Scholar
77. 1. Gomez-Lopez N
    2. Romero R
    3. Hassan SS
    4. Bhatti G
    5. Berry SM
    6. Kusanovic JP
    7. Pacora P
    8. Tarca AL

    (2019c) The cellular transcriptome in the maternal circulation during normal pregnancy: a longitudinal study

    Frontiers in Immunology 10:2863.

    https://doi.org/10.3389/fimmu.2019.02863

    • PubMed
    • Google Scholar
78. 1. Gomez-Lopez N
    2. Arenas-Hernandez M
    3. Romero R
    4. Miller D
    5. Garcia-Flores V
    6. Leng Y
    7. Xu Y
    8. Galaz J
    9. Hassan SS
    10. Hsu C-D
    11. Tse H
    12. Sanchez-Torres C
    13. Done B
    14. Tarca AL

    (2020) Regulatory t cells play a role in a subset of idiopathic preterm labor/birth and adverse neonatal outcomes

    Cell Reports 32:107874.

    https://doi.org/10.1016/j.celrep.2020.107874

    • Google Scholar
79. 1. Gomez-Lopez N
    2. Garcia-Flores V
    3. Chin PY
    4. Groome HM
    5. Bijland MT
    6. Diener KR
    7. Romero R
    8. Robertson SA

    (2021) Macrophages exert homeostatic actions in pregnancy to protect against preterm birth and fetal inflammatory injury

    JCI Insight 6:e146089.

    https://doi.org/10.1172/jci.insight.146089

    • PubMed
    • Google Scholar
80. 1. Gomez-Lopez N
    2. Galaz J
    3. Miller D
    4. Farias-Jofre M
    5. Liu Z
    6. Arenas-Hernandez M
    7. Garcia-Flores V
    8. Shaffer Z
    9. Greenberg JM
    10. Theis KR
    11. Romero R

    (2022a) The immunobiology of preterm labor and birth: intra-amniotic inflammation or breakdown of maternal-fetal homeostasis

    Reproduction 164:R11–R45.

    https://doi.org/10.1530/REP-22-0046

    • PubMed
    • Google Scholar
81. 1. Gomez-Lopez N
    2. Romero R
    3. Galaz J
    4. Bhatti G
    5. Done B
    6. Miller D
    7. Ghita C
    8. Motomura K
    9. Farias-Jofre M
    10. Jung E
    11. Pique-Regi R
    12. Hassan SS
    13. Chaiworapongsa T
    14. Tarca AL

    (2022b) Transcriptome changes in maternal peripheral blood during term parturition mimic perturbations preceding spontaneous preterm birth†

    Biology of Reproduction 106:185–199.

    https://doi.org/10.1093/biolre/ioab197

    • PubMed
    • Google Scholar
82. 1. Gomez‐Lopez N
    2. Olson DM
    3. Robertson SA

    (2016) Interleukin‐6 controls uterine Th9 cells and CD8 ⁺ T regulatory cells to accelerate parturition in mice

    Immunology & Cell Biology 94:79–89.

    https://doi.org/10.1038/icb.2015.63

    • Google Scholar
83. 1. González-Mesa E
    2. Blasco-Alonso M
    3. Benítez MJ
    4. Gómez-Muñoz C
    5. Sabonet-Morente L
    6. Gómez-Castellanos M
    7. Ulloa O
    8. González-Cazorla E
    9. Puertas-Prieto A
    10. Mozas-Moreno J
    11. Jiménez-López J
    12. Lubián-López D

    (2021) Obstetric and perinatal outcomes after very early preterm premature rupture of membranes (PPROM)-a retrospective analysis over the period 2000-2020

    Medicina 57:469.

    https://doi.org/10.3390/medicina57050469

    • PubMed
    • Google Scholar
84. 1. Gordon S
    2. Taylor PR

    (2005) Monocyte and macrophage heterogeneity

    Nature Reviews Immunology 5:953–964.

    https://doi.org/10.1038/nri1733

    • Google Scholar
85. 1. Goya M
    2. Bernabeu A
    3. García N
    4. Plata J
    5. Gonzalez F
    6. Merced C
    7. Llurba E
    8. Suy A
    9. Casellas M
    10. Carreras E
    11. Cabero L

    (2013) Premature rupture of membranes before 34 weeks managed expectantly: maternal and perinatal outcomes in singletons

    The Journal of Maternal-Fetal & Neonatal Medicine 26:290–293.

    https://doi.org/10.3109/14767058.2012.733779

    • Google Scholar
86. 1. Gravett MG
    2. Witkin SS
    3. Haluska GJ
    4. Edwards JL
    5. Cook MJ
    6. Novy MJ

    (1994) An experimental model for intraamniotic infection and preterm labor in rhesus monkeys

    American Journal of Obstetrics and Gynecology 171:1660–1667.

    https://doi.org/10.1016/0002-9378(94)90418-9

    • Google Scholar
87. 1. Grewal K
    2. Lee YS
    3. Smith A
    4. Brosens JJ
    5. Bourne T
    6. Al-Memar M
    7. Kundu S
    8. MacIntyre DA
    9. Bennett PR

    (2022) Chromosomally normal miscarriage is associated with vaginal dysbiosis and local inflammation

    BMC Medicine 20:38.

    https://doi.org/10.1186/s12916-021-02227-7

    • PubMed
    • Google Scholar
88. 1. Griffith JW
    2. Sokol CL
    3. Luster AD

    (2014) Chemokines and chemokine receptors: positioning cells for host defense and immunity

    Annual Review of Immunology 32:659–702.

    https://doi.org/10.1146/annurev-immunol-032713-120145

    • Google Scholar
89. 1. Gudicha DW
    2. Romero R
    3. Kabiri D
    4. Hernandez-Andrade E
    5. Pacora P
    6. Erez O
    7. Kusanovic JP
    8. Jung E
    9. Paredes C
    10. Berry SM
    11. Yeo L
    12. Hassan SS
    13. Hsu CD
    14. Tarca AL

    (2021) Personalized assessment of cervical length improves prediction of spontaneous preterm birth: a standard and a percentile calculator

    American Journal of Obstetrics and Gynecology 224:288.

    https://doi.org/10.1016/j.ajog.2020.09.002

    • PubMed
    • Google Scholar
90. 1. Guilliams M
    2. Mildner A
    3. Yona S

    (2018) Developmental and functional heterogeneity of monocytes

    Immunity 49:595–613.

    https://doi.org/10.1016/j.immuni.2018.10.005

    • Google Scholar
91. 1. Haguenoer K
    2. Sengchanh S
    3. Gaudy-Graffin C
    4. Boyard J
    5. Fontenay R
    6. Marret H
    7. Goudeau A
    8. Pigneaux de Laroche N
    9. Rusch E
    10. Giraudeau B

    (2014) Vaginal self-sampling is a cost-effective way to increase participation in a cervical cancer screening programme: a randomised trial

    British Journal of Cancer 111:2187–2196.

    https://doi.org/10.1038/bjc.2014.510

    • PubMed
    • Google Scholar
92. 1. Hamilton JA

    (2008) Colony-stimulating factors in inflammation and autoimmunity

    Nature Reviews. Immunology 8:533–544.

    https://doi.org/10.1038/nri2356

    • PubMed
    • Google Scholar
93. 1. Harder J
    2. Bartels J
    3. Christophers E
    4. Schröder JM

    (1997) A peptide antibiotic from human skin

    Nature 387:861.

    https://doi.org/10.1038/43088

    • PubMed
    • Google Scholar
94. 1. Hassan SS
    2. Romero R
    3. Berry SM
    4. Dang K
    5. Blackwell SC
    6. Treadwell MC
    7. Wolfe HM

    (2000) Patients with an ultrasonographic cervical length < or =15 mm have nearly a 50% risk of early spontaneous preterm delivery

    American Journal of Obstetrics and Gynecology 182:1458–1467.

    https://doi.org/10.1067/mob.2000.106851

    • PubMed
    • Google Scholar
95. 1. Hassan SS
    2. Romero R
    3. Vidyadhari D
    4. Fusey S
    5. Baxter JK
    6. Khandelwal M
    7. Vijayaraghavan J
    8. Trivedi Y
    9. Soma-Pillay P
    10. Sambarey P
    11. Dayal A
    12. Potapov V
    13. O’Brien J
    14. Astakhov V
    15. Yuzko O
    16. Kinzler W
    17. Dattel B
    18. Sehdev H
    19. Mazheika L
    20. Manchulenko D
    21. Gervasi MT
    22. Sullivan L
    23. Conde-Agudelo A
    24. Phillips JA
    25. Creasy GW

    (2011) Vaginal progesterone reduces the rate of preterm birth in women with a sonographic short cervix: a multicenter, randomized, double-blind, placebo-controlled trial

    Ultrasound in Obstetrics & Gynecology 38:18–31.

    https://doi.org/10.1002/uog.9017

    • PubMed
    • Google Scholar
96. 1. Haviland MJ
    2. Shainker SA
    3. Hacker MR
    4. Burris HH

    (2016) Racial and ethnic disparities in universal cervical length screening with transvaginal ultrasound

    The Journal of Maternal-Fetal & Neonatal Medicine 29:4078–4081.

    https://doi.org/10.3109/14767058.2016.1157577

    • PubMed
    • Google Scholar
97. 1. Hazuda DJ
    2. Lee JC
    3. Young PR

    (1988) The kinetics of interleukin 1 secretion from activated monocytes: differences between interleukin 1 alpha and interleukin 1 beta

    Journal of Biological Chemistry 263:8473–8479.

    https://doi.org/10.1016/S0021-9258(18)68502-3

    • Google Scholar
98. 1. Heath VCF
    2. Southall TR
    3. Souka AP
    4. Elisseou A
    5. Nicolaides KH

    (1998) Cervical length at 23 weeks of gestation: prediction of spontaneous preterm delivery

    Ultrasound in Obstetrics & Gynecology 12:312–317.

    https://doi.org/10.1046/j.1469-0705.1998.12050312.x

    • Google Scholar
99. 1. Hein M
    2. Valore EV
    3. Helmig RB
    4. Uldbjerg N
    5. Ganz T

    (2002) Antimicrobial factors in the cervical mucus plug

    American Journal of Obstetrics and Gynecology 187:137–144.

    https://doi.org/10.1067/mob.2002.123034

    • Google Scholar
100. 1. Henney CS

     (1989) Interleukin 7: effects on early events in lymphopoiesis

     Immunology Today 10:170–173.

     https://doi.org/10.1016/0167-5699(89)90175-8

     • Google Scholar
101. 1. Hezelgrave NL
     2. Seed PT
     3. Chin-Smith EC
     4. Ridout AE
     5. Shennan AH
     6. Tribe RM

     (2020) Cervicovaginal natural antimicrobial expression in pregnancy and association with spontaneous preterm birth

     Scientific Reports 10:12018.

     https://doi.org/10.1038/s41598-020-68329-z

     • PubMed
     • Google Scholar
102. 1. Hočevar K
     2. Maver A
     3. Vidmar Šimic M
     4. Hodžić A
     5. Haslberger A
     6. Premru Seršen T
     7. Peterlin B

     (2019) Vaginal microbiome signature is associated with spontaneous preterm delivery

     Frontiers in Medicine 6:201.

     https://doi.org/10.3389/fmed.2019.00201

     • PubMed
     • Google Scholar
103. 1. Hugues S
     2. Scholer A
     3. Boissonnas A
     4. Nussbaum A
     5. Combadière C
     6. Amigorena S
     7. Fetler L

     (2007) Dynamic imaging of chemokine-dependent CD8+ T cell help for CD8+ T cell responses

     Nature Immunology 8:921–930.

     https://doi.org/10.1038/ni1495

     • Google Scholar
104. 1. Iams JD
     2. Goldenberg RL
     3. Meis PJ
     4. Mercer BM
     5. Moawad A
     6. Das A
     7. Thom E
     8. McNellis D
     9. Copper RL
     10. Johnson F
     11. Roberts JM

     (1996) The length of the cervix and the risk of spontaneous premature delivery

     New England Journal of Medicine 334:567–573.

     https://doi.org/10.1056/NEJM199602293340904

     • Google Scholar
105. 1. Iams JD
     2. Grobman WA
     3. Lozitska A
     4. Spong CY
     5. Saade G
     6. Mercer BM
     7. Tita AT
     8. Rouse DJ
     9. Sorokin Y
     10. Wapner RJ
     11. Leveno KJ
     12. Blackwell SC
     13. Esplin MS
     14. Tolosa JE
     15. Thorp JM
     16. Caritis SN
     17. Van Dorsten PJ

     (2013) Adherence to criteria for transvaginal ultrasound imaging and measurement of cervical length

     American Journal of Obstetrics and Gynecology 209:365.

     https://doi.org/10.1016/j.ajog.2013.07.032

     • PubMed
     • Google Scholar
106. 1. Imseis HM
     2. Greig PC
     3. Livengood CH
     4. Shunior E
     5. Durda P
     6. Erikson M

     (1997)

     Characterization of the inflammatory cytokines in the vagina during pregnancy and labor and with bacterial vaginosis

     Journal of the Society for Gynecologic Investigation 4:90–94.

     • PubMed
     • Google Scholar
107. 1. Itaoka N
     2. Nagamatsu T
     3. Schust DJ
     4. Ichikawa M
     5. Sayama S
     6. Iwasawa-Kawai Y
     7. Kawana K
     8. Yamashita T
     9. Osuga Y
     10. Fujii T

     (2015) Cervical expression of elafin and slpi in pregnancy and their association with preterm labor

     American Journal of Reproductive Immunology 73:536–544.

     https://doi.org/10.1111/aji.12354

     • PubMed
     • Google Scholar
108. 1. Jain VG
     2. Monangi N
     3. Zhang G
     4. Muglia LJ

     (2022) Genetics, epigenetics, and transcriptomics of preterm birth

     American Journal of Reproductive Immunology 88:e13600.

     https://doi.org/10.1111/aji.13600

     • PubMed
     • Google Scholar
109. 1. Jehan F
     2. Sazawal S
     3. Baqui AH
     4. Nisar MI
     5. Dhingra U
     6. Khanam R
     7. Ilyas M
     8. Dutta A
     9. Mitra DK
     10. Mehmood U
     11. Deb S
     12. Mahmud A
     13. Hotwani A
     14. Ali SM
     15. Rahman S
     16. Nizar A
     17. Ame SM
     18. Moin MI
     19. Muhammad S
     20. Chauhan A
     21. Begum N
     22. Khan W
     23. Das S
     24. Ahmed S
     25. Hasan T
     26. Khalid J
     27. Rizvi SJR
     28. Juma MH
     29. Chowdhury NH
     30. Kabir F
     31. Aftab F
     32. Quaiyum A
     33. Manu A
     34. Yoshida S
     35. Bahl R
     36. Rahman A
     37. Pervin J
     38. Winston J
     39. Musonda P
     40. Stringer JSA
     41. Litch JA
     42. Ghaemi MS
     43. Moufarrej MN
     44. Contrepois K
     45. Chen S
     46. Stelzer IA
     47. Stanley N
     48. Chang AL
     49. Hammad GB
     50. Wong RJ
     51. Liu C
     52. Quaintance CC
     53. Culos A
     54. Espinosa C
     55. Xenochristou M
     56. Becker M
     57. Fallahzadeh R
     58. Ganio E
     59. Tsai AS
     60. Gaudilliere D
     61. Tsai ES
     62. Han X
     63. Ando K
     64. Tingle M
     65. Maric I
     66. Wise PH
     67. Winn VD
     68. Druzin ML
     69. Gibbs RS
     70. Darmstadt GL
     71. Murray JC
     72. Shaw GM
     73. Stevenson DK
     74. Snyder MP
     75. Quake SR
     76. Angst MS
     77. Gaudilliere B
     78. Aghaeepour N

     (2020) Multiomics characterization of preterm birth in low- and middle-income countries

     JAMA Network Open 3:e2029655.

     https://doi.org/10.1001/jamanetworkopen.2020.29655

     • PubMed
     • Google Scholar
110. 1. Jones SA
     2. Jenkins BJ

     (2018) Recent insights into targeting the IL-6 cytokine family in inflammatory diseases and cancer

     Nature Reviews Immunology 18:773–789.

     https://doi.org/10.1038/s41577-018-0066-7

     • Google Scholar
111. 1. Jung EY
     2. Park JW
     3. Ryu A
     4. Lee SY
     5. Cho SH
     6. Park KH

     (2016) Prediction of impending preterm delivery based on sonographic cervical length and different cytokine levels in cervicovaginal fluid in preterm labor

     The Journal of Obstetrics and Gynaecology Research 42:158–165.

     https://doi.org/10.1111/jog.12882

     • PubMed
     • Google Scholar
112. 1. Kacerovsky M
     2. Musilova I
     3. Jacobsson B
     4. Drahosova M
     5. Hornychova H
     6. Janku P
     7. Prochazka M
     8. Simetka O
     9. Andrys C

     (2015) Vaginal fluid IL-6 and IL-8 levels in pregnancies complicated by preterm prelabor membrane ruptures

     The Journal of Maternal-Fetal & Neonatal Medicine 28:392–398.

     https://doi.org/10.3109/14767058.2014.917625

     • Google Scholar
113. 1. Kalinka J
     2. Sobala W
     3. Wasiela M
     4. Brzezińska‐Błaszczyk E

     (2005) Decreased proinflammatory cytokines in cervicovaginal fluid, as measured in midgestation, are associated with preterm delivery

     American Journal of Reproductive Immunology 54:70–76.

     https://doi.org/10.1111/j.1600-0897.2005.00289.x

     • Google Scholar
114. 1. Kato K
     2. Shimozato O
     3. Hoshi K
     4. Wakimoto H
     5. Hamada H
     6. Yagita H
     7. Okumura K

     (1996) Local production of the p40 subunit of interleukin 12 suppresses T-helper 1-mediated immune responses and prevents allogeneic myoblast rejection

     PNAS 93:9085–9089.

     https://doi.org/10.1073/pnas.93.17.9085

     • PubMed
     • Google Scholar
115. 1. Kim CJ
     2. Romero R
     3. Kusanovic JP
     4. Yoo W
     5. Dong Z
     6. Topping V
     7. Gotsch F
     8. Yoon BH
     9. Chi JG
     10. Kim JS

     (2010) The frequency, clinical significance, and pathological features of chronic chorioamnionitis: a lesion associated with spontaneous preterm birth

     Modern Pathology 23:1000–1011.

     https://doi.org/10.1038/modpathol.2010.73

     • PubMed
     • Google Scholar
116. 1. Kim CJ
     2. Romero R
     3. Chaemsaithong P
     4. Chaiyasit N
     5. Yoon BH
     6. Kim YM

     (2015a) Acute chorioamnionitis and funisitis: definition, pathologic features, and clinical significance

     American Journal of Obstetrics and Gynecology 213:S29–S52.

     https://doi.org/10.1016/j.ajog.2015.08.040

     • PubMed
     • Google Scholar
117. 1. Kim CJ
     2. Romero R
     3. Chaemsaithong P
     4. Kim J-S

     (2015b) Chronic inflammation of the placenta: definition, classification, pathogenesis, and clinical significance

     American Journal of Obstetrics and Gynecology 213:S53–S69.

     https://doi.org/10.1016/j.ajog.2015.08.041

     • PubMed
     • Google Scholar
118. 1. Kim Y
     2. Lee KY
     3. Lee JJ
     4. Tak H
     5. Park ST
     6. Song JE
     7. Son GH

     (2022) Expression of antimicrobial peptides in the amniotic fluid of women with cervical insufficiency

     American Journal of Reproductive Immunology 88:e13577.

     https://doi.org/10.1111/aji.13577

     • PubMed
     • Google Scholar
119. 1. Kindinger LM
     2. Bennett PR
     3. Lee YS
     4. Marchesi JR
     5. Smith A
     6. Cacciatore S
     7. Holmes E
     8. Nicholson JK
     9. Teoh TG
     10. MacIntyre DA

     (2017) The interaction between vaginal microbiota, cervical length, and vaginal progesterone treatment for preterm birth risk

     Microbiome 5:6.

     https://doi.org/10.1186/s40168-016-0223-9

     • PubMed
     • Google Scholar
120. 1. King AE
     2. Critchley HOD
     3. Kelly RW

     (2003) Innate immune defences in the human endometrium

     Reproductive Biology and Endocrinology 1:116.

     https://doi.org/10.1186/1477-7827-1-116

     • PubMed
     • Google Scholar
121. 1. King AE
     2. Paltoo A
     3. Kelly RW
     4. Sallenave J-M
     5. Bocking AD
     6. Challis JRG

     (2007) Expression of natural antimicrobials by human placenta and fetal membranes

     Placenta 28:161–169.

     https://doi.org/10.1016/j.placenta.2006.01.006

     • Google Scholar
122. 1. Kostura MJ
     2. Tocci MJ
     3. Limjuco G
     4. Chin J
     5. Cameron P
     6. Hillman AG
     7. Chartrain NA
     8. Schmidt JA

     (1989) Identification of a monocyte specific pre-interleukin 1 beta convertase activity

     PNAS 86:5227–5231.

     https://doi.org/10.1073/pnas.86.14.5227

     • PubMed
     • Google Scholar
123. 1. Kumar M
     2. Murugesan S
     3. Singh P
     4. Saadaoui M
     5. Elhag DA
     6. Terranegra A
     7. Kabeer BSA
     8. Marr AK
     9. Kino T
     10. Brummaier T
     11. McGready R
     12. Nosten F
     13. Chaussabel D
     14. Al Khodor S

     (2021) Vaginal microbiota and cytokine levels predict preterm delivery in asian women

     Frontiers in Cellular and Infection Microbiology 11:639665.

     https://doi.org/10.3389/fcimb.2021.639665

     • PubMed
     • Google Scholar
124. 1. Kuziel WA
     2. Morgan SJ
     3. Dawson TC
     4. Griffin S
     5. Smithies O
     6. Ley K
     7. Maeda N

     (1997) Severe reduction in leukocyte adhesion and monocyte extravasation in mice deficient in CC chemokine receptor 2

     PNAS 94:12053–12058.

     https://doi.org/10.1073/pnas.94.22.12053

     • PubMed
     • Google Scholar
125. 1. Lal BK
     2. Varma S
     3. Pappas PJ
     4. Hobson RW
     5. Durán WN

     (2001) VEGF increases permeability of the endothelial cell monolayer by activation of PKB/akt, endothelial nitric-oxide synthase, and MAP kinase pathways

     Microvascular Research 62:252–262.

     https://doi.org/10.1006/mvre.2001.2338

     • PubMed
     • Google Scholar
126. 1. Lee SK
     2. Kim CJ
     3. Kim D-J
     4. Kang J

     (2015) Immune cells in the female reproductive tract

     Immune Network 15:16.

     https://doi.org/10.4110/in.2015.15.1.16

     • Google Scholar
127. 1. Lichtenstein A

     (1991) Mechanism of mammalian cell lysis mediated by peptide defensins: evidence for an initial alteration of the plasma membrane

     The Journal of Clinical Investigation 88:93–100.

     https://doi.org/10.1172/JCI115310

     • PubMed
     • Google Scholar
128. 1. Lunny C
     2. Taylor D
     3. Hoang L
     4. Wong T
     5. Gilbert M
     6. Lester R
     7. Krajden M
     8. Ogilvie G

     (2015) Self-collected versus clinician-collected sampling for chlamydia and gonorrhea screening: a systemic review and meta-analysis

     PLOS ONE 10:e0132776.

     https://doi.org/10.1371/journal.pone.0132776

     • PubMed
     • Google Scholar
129. 1. Maisetta G
     2. Batoni G
     3. Esin S
     4. Luperini F
     5. Pardini M
     6. Bottai D
     7. Florio W
     8. Giuca MR
     9. Gabriele M
     10. Campa M

     (2003) Activity of human beta-defensin 3 alone or combined with other antimicrobial agents against oral bacteria

     Antimicrobial Agents and Chemotherapy 47:3349–3351.

     https://doi.org/10.1128/AAC.47.10.3349-3351.2003

     • PubMed
     • Google Scholar
130. 1. Martin JA
     2. Osterman MJK

     (2018)

     Describing the increase in preterm births in the United States, 2014-2016

     NCHS Data Brief 01:1–8.

     • PubMed
     • Google Scholar
131. Book

     1. Martin JA
     2. Hamilton BE

     (2021)

     Births in the United States

     NCHS Data Brief.

     • Google Scholar
132. 1. Mattner F
     2. Fischer S
     3. Guckes S
     4. Jin S
     5. Kaulen H
     6. Schmitt E
     7. Rüde E
     8. Germann T

     (1993) The interleukin-12 subunit p40 specifically inhibits effects of the interleukin-12 heterodimer

     European Journal of Immunology 23:2202–2208.

     https://doi.org/10.1002/eji.1830230923

     • PubMed
     • Google Scholar
133. 1. Mei C
     2. Yang W
     3. Wei X
     4. Wu K
     5. Huang D

     (2019) The unique microbiome and innate immunity during pregnancy

     Frontiers in Immunology 10:2886.

     https://doi.org/10.3389/fimmu.2019.02886

     • PubMed
     • Google Scholar
134. 1. Menon R
     2. Richardson LS

     (2017) Preterm prelabor rupture of the membranes: a disease of the fetal membranes

     Seminars in Perinatology 41:409–419.

     https://doi.org/10.1053/j.semperi.2017.07.012

     • PubMed
     • Google Scholar
135. 1. Mikołajczyk M
     2. Wirstlein P
     3. Adamczyk M
     4. Skrzypczak J
     5. Wender-Ożegowska E

     (2020) Value of cervicovaginal fluid cytokines in prediction of fetal inflammatory response syndrome in pregnancies complicated with preterm premature rupture of membranes (pPROM)

     Journal of Perinatal Medicine 48:249–255.

     https://doi.org/10.1515/jpm-2019-0280

     • Google Scholar
136. 1. Modi BP
     2. Teves ME
     3. Pearson LN
     4. Parikh HI
     5. Haymond-Thornburg H
     6. Tucker JL
     7. Chaemsaithong P
     8. GomezLopez N
     9. York TP
     10. Romero R
     11. Strauss JF

     (2017) Mutations in fetal genes involved in innate immunity and host defense against microbes increase risk of preterm premature rupture of membranes (PPROM)

     Molecular Genetics & Genomic Medicine 5:720–729.

     https://doi.org/10.1002/mgg3.330

     • PubMed
     • Google Scholar
137. 1. Modi BP
     2. Parikh HI
     3. Teves ME
     4. Kulkarni R
     5. Liyu J
     6. Romero R
     7. York TP
     8. Strauss JF

     (2018) Discovery of rare ancestry-specific variants in the fetal genome that confer risk of preterm premature rupture of membranes (PPROM) and preterm birth

     BMC Medical Genetics 19:181.

     https://doi.org/10.1186/s12881-018-0696-4

     • PubMed
     • Google Scholar
138. 1. Monin L
     2. Whettlock EM
     3. Male V

     (2020) Immune responses in the human female reproductive tract

     Immunology 160:106–115.

     https://doi.org/10.1111/imm.13136

     • PubMed
     • Google Scholar
139. 1. Motomura K
     2. Romero R
     3. Garcia-Flores V
     4. Leng Y
     5. Xu Y
     6. Galaz J
     7. Slutsky R
     8. Levenson D
     9. GomezLopez N

     (2020) The alarmin interleukin-1α causes preterm birth through the NLRP3 inflammasome

     Molecular Human Reproduction 26:712–726.

     https://doi.org/10.1093/molehr/gaaa054

     • PubMed
     • Google Scholar
140. 1. Motomura K
     2. Romero R
     3. Plazyo O
     4. Garcia-Flores V
     5. Gershater M
     6. Galaz J
     7. Miller D
     8. GomezLopez N

     (2021) The alarmin S100A12 causes sterile inflammation of the human chorioamniotic membranes as well as preterm birth and neonatal mortality in mice†

     Biology of Reproduction 105:1494–1509.

     https://doi.org/10.1093/biolre/ioab188

     • PubMed
     • Google Scholar
141. 1. Motomura K
     2. Romero R
     3. Galaz J
     4. Tao L
     5. Garcia-Flores V
     6. Xu Y
     7. Done B
     8. Arenas-Hernandez M
     9. Miller D
     10. Gutierrez-Contreras P
     11. Farias-Jofre M
     12. Aras S
     13. Grossman LI
     14. Tarca AL
     15. Gomez-Lopez N

     (2022) Fetal and maternal NLRP3 signaling is required for preterm labor and birth

     JCI Insight 7:e158238.

     https://doi.org/10.1172/jci.insight.158238

     • PubMed
     • Google Scholar
142. 1. Ngo TTM
     2. Moufarrej MN
     3. Rasmussen M-LH
     4. Camunas-Soler J
     5. Pan W
     6. Okamoto J
     7. Neff NF
     8. Liu K
     9. Wong RJ
     10. Downes K
     11. Tibshirani R
     12. Shaw GM
     13. Skotte L
     14. Stevenson DK
     15. Biggio JR
     16. Elovitz MA
     17. Melbye M
     18. Quake SR

     (2018) Noninvasive blood tests for fetal development predict gestational age and preterm delivery

     Science 360:1133–1136.

     https://doi.org/10.1126/science.aar3819

     • PubMed
     • Google Scholar
143. 1. Odogwu NM
     2. Chen J
     3. Onebunne CA
     4. Jeraldo P
     5. Yang L
     6. Johnson S
     7. Ayeni FA
     8. Walther-Antonio MRS
     9. Olayemi OO
     10. Chia N
     11. Omigbodun AO

     (2021) Predominance of atopobium vaginae at midtrimester: a potential indicator of preterm birth risk in a nigerian cohort

     mSphere 6:e01261-20.

     https://doi.org/10.1128/mSphere.01261-20

     • PubMed
     • Google Scholar
144. 1. Oh JE
     2. Iijima N
     3. Song E
     4. Lu P
     5. Klein J
     6. Jiang R
     7. Kleinstein SH
     8. Iwasaki A

     (2019) Migrant memory B cells secrete luminal antibody in the vagina

     Nature 571:122–126.

     https://doi.org/10.1038/s41586-019-1285-1

     • PubMed
     • Google Scholar
145. 1. Osman I

     (2003) Leukocyte density and pro-inflammatory cytokine expression in human fetal membranes, decidua, cervix and myometrium before and during labour at term

     Molecular Human Reproduction 9:41–45.

     https://doi.org/10.1093/molehr/gag001

     • Google Scholar
146. 1. Payne MS
     2. Newnham JP
     3. Doherty DA
     4. Furfaro LL
     5. Pendal NL
     6. Loh DE
     7. Keelan JA

     (2021) A specific bacterial DNA signature in the vagina of Australian women in midpregnancy predicts high risk of spontaneous preterm birth (the Predict1000 study)

     American Journal of Obstetrics and Gynecology 224:206.

     https://doi.org/10.1016/j.ajog.2020.08.034

     • PubMed
     • Google Scholar
147. 1. Pedretti MK
     2. Kazemier BM
     3. Dickinson JE
     4. Mol BWJ

     (2017) Implementing universal cervical length screening in asymptomatic women with singleton pregnancies: challenges and opportunities

     The Australian & New Zealand Journal of Obstetrics & Gynaecology 57:221–227.

     https://doi.org/10.1111/ajo.12586

     • PubMed
     • Google Scholar
148. 1. Peterson LS
     2. Stelzer IA
     3. Tsai AS
     4. Ghaemi MS
     5. Han X
     6. Ando K
     7. Winn VD
     8. Martinez NR
     9. Contrepois K
     10. Moufarrej MN
     11. Quake S
     12. Relman DA
     13. Snyder MP
     14. Shaw GM
     15. Stevenson DK
     16. Wong RJ
     17. Arck P
     18. Angst MS
     19. Aghaeepour N
     20. Gaudilliere B

     (2020) Multiomic immune clockworks of pregnancy

     Seminars in Immunopathology 42:397–412.

     https://doi.org/10.1007/s00281-019-00772-1

     • PubMed
     • Google Scholar
149. 1. Pinto S
     2. Malheiro MF
     3. Vaz A
     4. Rodrigues T
     5. Montenegro N
     6. Guimarães H

     (2019) Neonatal outcome in preterm deliveries before 34-week gestation – the influence of the mechanism of labor onset

     The Journal of Maternal-Fetal & Neonatal Medicine 32:3655–3661.

     https://doi.org/10.1080/14767058.2018.1481038

     • Google Scholar
150. 1. Plazyo O
     2. Romero R
     3. Unkel R
     4. Balancio A
     5. Mial TN
     6. Xu Y
     7. Dong Z
     8. Hassan SS
     9. Gomez-Lopez N

     (2016) HMGB1 induces an inflammatory response in the chorioamniotic membranes that is partially mediated by the inflammasome

     Biology of Reproduction 95:130.

     https://doi.org/10.1095/biolreprod.116.144139

     • PubMed
     • Google Scholar
151. 1. Polettini J
     2. Silva MG
     3. Kacerovsky M
     4. Syed TA
     5. Saade G
     6. Menon R

     (2014) Expression profiles of fetal membrane nicotinamide adenine dinucleotide phosphate oxidases (NOX) 2 and 3 differentiates spontaneous preterm birth and pPROM pathophysiologies

     Placenta 35:188–194.

     https://doi.org/10.1016/j.placenta.2013.12.012

     • PubMed
     • Google Scholar
152. 1. Presicce P
     2. Senthamaraikannan P
     3. Alvarez M
     4. Rueda CM
     5. Cappelletti M
     6. Miller LA
     7. Jobe AH
     8. Chougnet CA
     9. Kallapur SG

     (2015) Neutrophil recruitment and activation in decidua with intra-amniotic IL-1beta in the preterm rhesus macaque

     Biology of Reproduction 92:56.

     https://doi.org/10.1095/biolreprod.114.124420

     • PubMed
     • Google Scholar
153. 1. Pruski P
     2. Correia GDS
     3. Lewis HV
     4. Capuccini K
     5. Inglese P
     6. Chan D
     7. Brown RG
     8. Kindinger L
     9. Lee YS
     10. Smith A
     11. Marchesi J
     12. McDonald JAK
     13. Cameron S
     14. Alexander-Hardiman K
     15. David AL
     16. Stock SJ
     17. Norman JE
     18. Terzidou V
     19. Teoh TG
     20. Sykes L
     21. Bennett PR
     22. Takats Z
     23. MacIntyre DA

     (2021) Direct on-swab metabolic profiling of vaginal microbiome host interactions during pregnancy and preterm birth

     Nature Communications 12:5967.

     https://doi.org/10.1038/s41467-021-26215-w

     • PubMed
     • Google Scholar
154. 1. Ravel J
     2. Gajer P
     3. Abdo Z
     4. Schneider GM
     5. Koenig SSK
     6. McCulle SL
     7. Karlebach S
     8. Gorle R
     9. Russell J
     10. Tacket CO
     11. Brotman RM
     12. Davis CC
     13. Ault K
     14. Peralta L
     15. Forney LJ

     (2011) Vaginal microbiome of reproductive-age women

     PNAS 108 Suppl 1:4680–4687.

     https://doi.org/10.1073/pnas.1002611107

     • PubMed
     • Google Scholar
155. Software

     1. R Development Core Team

     (2010) R: A language and environment for statistical Compuiting

     R Foundation for Statistical Computing, Vienna, Austria.

     https://www.r-project.org
156. 1. Redline RW

     (2015) Classification of placental lesions

     American Journal of Obstetrics and Gynecology 213:S21–S28.

     https://doi.org/10.1016/j.ajog.2015.05.056

     • Google Scholar
157. 1. Robertson SA
     2. Christiaens I
     3. Dorian CL
     4. Zaragoza DB
     5. Care AS
     6. Banks AM
     7. Olson DM

     (2010) Interleukin-6 is an essential determinant of on-time parturition in the mouse

     Endocrinology 151:3996–4006.

     https://doi.org/10.1210/en.2010-0063

     • Google Scholar
158. 1. Robinson A
     2. Han CZ
     3. Glass CK
     4. Pollard JW

     (2021) Monocyte regulation in homeostasis and malignancy

     Trends in Immunology 42:104–119.

     https://doi.org/10.1016/j.it.2020.12.001

     • PubMed
     • Google Scholar
159. 1. Romero R
     2. Brody DT
     3. Oyarzun E
     4. Mazor M
     5. King Wu Y
     6. Hobbins JC
     7. Durum SK

     (1989) Infection and labor

     American Journal of Obstetrics and Gynecology 160:1117–1123.

     https://doi.org/10.1016/0002-9378(89)90172-5

     • Google Scholar
160. 1. Romero R
     2. Mazor M
     3. Brandt F
     4. Sepulveda W
     5. Avila C
     6. Cotton DB
     7. Dinarello CA

     (1992a) Interleukin-1 alpha and interleukin-1 beta in preterm and term human parturition

     American Journal of Reproductive Immunology 27:117–123.

     https://doi.org/10.1111/j.1600-0897.1992.tb00737.x

     • PubMed
     • Google Scholar
161. 1. Romero R
     2. Tartakovsky B

     (1992b) The natural interleukin-1 receptor antagonist prevents interleukin-l-induced preterm delivery in mice

     American Journal of Obstetrics and Gynecology 167:1041–1045.

     https://doi.org/10.1016/S0002-9378(12)80035-4

     • Google Scholar
162. 1. Romero R
     2. Espinoza J
     3. Gonçalves LF
     4. Kusanovic JP
     5. Friel LA
     6. Nien JK

     (2006a) Inflammation in preterm and term labour and delivery

     Seminars in Fetal & Neonatal Medicine 11:317–326.

     https://doi.org/10.1016/j.siny.2006.05.001

     • PubMed
     • Google Scholar
163. 1. Romero R
     2. Espinoza J
     3. Kusanovic JP
     4. Gotsch F
     5. Hassan S
     6. Erez O
     7. Chaiworapongsa T
     8. Mazor M

     (2006b) The preterm parturition syndrome

     BJOG 113 Suppl 3:17–42.

     https://doi.org/10.1111/j.1471-0528.2006.01120.x

     • PubMed
     • Google Scholar
164. 1. Romero R
     2. Espinoza J
     3. Gonçalves LF
     4. Kusanovic JP
     5. Friel L
     6. Hassan S

     (2007) The role of inflammation and infection in preterm birth

     Seminars in Reproductive Medicine 25:21–39.

     https://doi.org/10.1055/s-2006-956773

     • PubMed
     • Google Scholar
165. 1. Romero R
     2. Dey SK
     3. Fisher SJ

     (2014a) Preterm labor: one syndrome, many causes

     Science 345:760–765.

     https://doi.org/10.1126/science.1251816

     • PubMed
     • Google Scholar
166. 1. Romero R
     2. Yeo L
     3. Chaemsaithong P
     4. Chaiworapongsa T
     5. Hassan SS

     (2014b) Progesterone to prevent spontaneous preterm birth

     Seminars in Fetal & Neonatal Medicine 19:15–26.

     https://doi.org/10.1016/j.siny.2013.10.004

     • PubMed
     • Google Scholar
167. 1. Romero R
     2. Nicolaides KH
     3. Conde-Agudelo A
     4. O’Brien JM
     5. Cetingoz E
     6. Da Fonseca E
     7. Creasy GW
     8. Hassan SS

     (2016) Vaginal progesterone decreases preterm birth ≤ 34 weeks of gestation in women with a singleton pregnancy and a short cervix: an updated meta-analysis including data from the OPPTIMUM study

     Ultrasound in Obstetrics & Gynecology 48:308–317.

     https://doi.org/10.1002/uog.15953

     • PubMed
     • Google Scholar
168. 1. Romero R
     2. Conde-Agudelo A
     3. El-Refaie W
     4. Rode L
     5. Brizot ML
     6. Cetingoz E
     7. Serra V
     8. Da Fonseca E
     9. Abdelhafez MS
     10. Tabor A
     11. Perales A
     12. Hassan SS
     13. Nicolaides KH

     (2017) Vaginal progesterone decreases preterm birth and neonatal morbidity and mortality in women with a twin gestation and a short cervix: an updated meta-analysis of individual patient data

     Ultrasound in Obstetrics & Gynecology 49:303–314.

     https://doi.org/10.1002/uog.17397

     • PubMed
     • Google Scholar
169. 1. Romero R
     2. Conde-Agudelo A
     3. Da Fonseca E
     4. O’Brien JM
     5. Cetingoz E
     6. Creasy GW
     7. Hassan SS
     8. Nicolaides KH

     (2018) Vaginal progesterone for preventing preterm birth and adverse perinatal outcomes in singleton gestations with a short cervix: a meta-analysis of individual patient data

     American Journal of Obstetrics and Gynecology 218:161–180.

     https://doi.org/10.1016/j.ajog.2017.11.576

     • PubMed
     • Google Scholar
170. 1. Romero R
     2. Tarca A
     3. Gomez-Lopez N
     4. Winters A
     5. Panzer J
     6. Lin H
     7. Gudicha D
     8. Galaz J
     9. Farias-Jofre M
     10. Kracht D
     11. Chaiworapongsa T
     12. Jung E
     13. Gotsch F
     14. Suksai M
     15. Berry S
     16. Ravel J
     17. Peddada S
     18. Theis K

     (2022) The vaginal microbiota in early pregnancy identifies a subset of women at risk for early preterm prelabor rupture of membranes and preterm birth

     In Review 01:e402/v1.

     https://doi.org/10.21203/rs.3.rs-2359402/v1

     • Google Scholar
171. 1. Sadowsky DW
     2. Adams KM
     3. Gravett MG
     4. Witkin SS
     5. Novy MJ

     (2006) Preterm labor is induced by intraamniotic infusions of interleukin-1β and tumor necrosis factor-α but not by interleukin-6 or interleukin-8 in a nonhuman primate model

     American Journal of Obstetrics and Gynecology 195:1578–1589.

     https://doi.org/10.1016/j.ajog.2006.06.072

     • Google Scholar
172. 1. Savasan ZA
     2. Romero R
     3. Chaiworapongsa T
     4. Kusanovic JP
     5. Kim SK
     6. Mazaki-Tovi S
     7. Vaisbuch E
     8. Mittal P
     9. Ogge G
     10. Madan I
     11. Dong Z
     12. Yeo L
     13. Hassan SS

     (2010) Evidence in support of a role for anti-angiogenic factors in preterm prelabor rupture of membranes

     The Journal of Maternal-Fetal & Neonatal Medicine 23:828–841.

     https://doi.org/10.3109/14767050903440471

     • PubMed
     • Google Scholar
173. 1. Shi C
     2. Pamer EG

     (2011) Monocyte recruitment during infection and inflammation

     Nature Reviews. Immunology 11:762–774.

     https://doi.org/10.1038/nri3070

     • PubMed
     • Google Scholar
174. 1. Shimoya K
     2. Zhang Q
     3. Temma K
     4. Kimura T
     5. Tsujie T
     6. Tsutsui T
     7. Wasada K
     8. Kanzaki T
     9. Koyama M
     10. Murata Y

     (2006) Secretory leukocyte protease inhibitor levels in cervicovaginal secretion of elderly women

     Maturitas 54:141–148.

     https://doi.org/10.1016/j.maturitas.2004.02.019

     • Google Scholar
175. 1. Short CS
     2. Quinlan R
     3. Bennett P
     4. Shattock RJ
     5. Taylor GP

     (2018) Optimising the collection of female genital tract fluid for cytokine analysis in pregnant women

     Journal of Immunological Methods 458:15–20.

     https://doi.org/10.1016/j.jim.2018.03.014

     • PubMed
     • Google Scholar
176. 1. Short C-ES
     2. Quinlan RA
     3. Wang X
     4. Preda VG
     5. Smith A
     6. Marchesi JR
     7. Lee YS
     8. MacIntyre DA
     9. Bennett PR
     10. Taylor GP

     (2021) Vaginal microbiota, genital inflammation and extracellular matrix remodelling collagenase: mmp-9 in pregnant women with hiv, a potential preterm birth mechanism warranting further exploration

     Frontiers in Cellular and Infection Microbiology 11:750103.

     https://doi.org/10.3389/fcimb.2021.750103

     • PubMed
     • Google Scholar
177. 1. Smith LK
     2. Draper ES
     3. Manktelow BN
     4. Dorling JS
     5. Field DJ

     (2007) Socioeconomic inequalities in very preterm birth rates

     Archives of Disease in Childhood. Fetal and Neonatal Edition 92:F11–F14.

     https://doi.org/10.1136/adc.2005.090308

     • PubMed
     • Google Scholar
178. 1. Smith SB
     2. Ravel J

     (2017) The vaginal microbiota, host defence and reproductive physiology

     The Journal of Physiology 595:451–463.

     https://doi.org/10.1113/JP271694

     • PubMed
     • Google Scholar
179. 1. Soto E
     2. Espinoza J
     3. Nien JK
     4. Kusanovic JP
     5. Erez O
     6. Richani K
     7. Santolaya-Forgas J
     8. Romero R

     (2007) Human beta-defensin-2: a natural antimicrobial peptide present in amniotic fluid participates in the host response to microbial invasion of the amniotic cavity

     The Journal of Maternal-Fetal & Neonatal Medicine 20:15–22.

     https://doi.org/10.1080/14767050601036212

     • PubMed
     • Google Scholar
180. 1. Stelzer IA
     2. Ghaemi MS
     3. Han X
     4. Ando K
     5. Hédou JJ
     6. Feyaerts D
     7. Peterson LS
     8. Rumer KK
     9. Tsai ES
     10. Ganio EA
     11. Gaudillière DK
     12. Tsai AS
     13. Choisy B
     14. Gaigne LP
     15. Verdonk F
     16. Jacobsen D
     17. Gavasso S
     18. Traber GM
     19. Ellenberger M
     20. Stanley N
     21. Becker M
     22. Culos A
     23. Fallahzadeh R
     24. Wong RJ
     25. Darmstadt GL
     26. Druzin ML
     27. Winn VD
     28. Gibbs RS
     29. Ling XB
     30. Sylvester K
     31. Carvalho B
     32. Snyder MP
     33. Shaw GM
     34. Stevenson DK
     35. Contrepois K
     36. Angst MS
     37. Aghaeepour N
     38. Gaudillière B

     (2021) Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

     Science Translational Medicine 13:eabd9898.

     https://doi.org/10.1126/scitranslmed.abd9898

     • PubMed
     • Google Scholar
181. 1. Strauss JF
     2. Pearson LN

     (2018)

     Spontaneous preterm birth: advances toward the discovery of genetic predisposition

     American Journal of Obstetrics and Gynecology 218:294–314.

     • Google Scholar
182. 1. Swanson KV
     2. Deng M
     3. Ting JP-Y

     (2019) The NLRP3 inflammasome: molecular activation and regulation to therapeutics

     Nature Reviews. Immunology 19:477–489.

     https://doi.org/10.1038/s41577-019-0165-0

     • PubMed
     • Google Scholar
183. 1. Tabatabaei N
     2. Eren AM
     3. Barreiro LB
     4. Yotova V
     5. Dumaine A
     6. Allard C
     7. Fraser WD

     (2019) Vaginal microbiome in early pregnancy and subsequent risk of spontaneous preterm birth: a case-control study

     BJOG 126:349–358.

     https://doi.org/10.1111/1471-0528.15299

     • PubMed
     • Google Scholar
184. 1. Tarca AL
     2. Romero R
     3. Benshalom-Tirosh N
     4. Than NG
     5. Gudicha DW
     6. Done B
     7. Pacora P
     8. Chaiworapongsa T
     9. Panaitescu B
     10. Tirosh D
     11. Gomez-Lopez N
     12. Draghici S
     13. Hassan SS
     14. Erez O

     (2019) The prediction of early preeclampsia: Results from a longitudinal proteomics study

     PLOS ONE 14:e0217273.

     https://doi.org/10.1371/journal.pone.0217273

     • PubMed
     • Google Scholar
185. 1. Tarca AL
     2. Pataki BÁ
     3. Romero R
     4. Sirota M
     5. Guan Y
     6. Kutum R
     7. Gomez-Lopez N
     8. Done B
     9. Bhatti G
     10. Yu T
     11. Andreoletti G
     12. Chaiworapongsa T
     13. DREAM Preterm Birth Prediction Challenge Consortium
     14. Hassan SS
     15. Hsu CD
     16. Aghaeepour N
     17. Stolovitzky G
     18. Csabai I
     19. Costello JC

     (2021) Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth

     Cell Reports. Medicine 2:100323.

     https://doi.org/10.1016/j.xcrm.2021.100323

     • PubMed
     • Google Scholar
186. 1. Tarca AL
     2. Taran A
     3. Romero R
     4. Jung E
     5. Paredes C
     6. Bhatti G
     7. Ghita C
     8. Chaiworapongsa T
     9. Than NG
     10. Hsu C-D

     (2022) Prediction of preeclampsia throughout gestation with maternal characteristics and biophysical and biochemical markers: a longitudinal study

     American Journal of Obstetrics and Gynecology 226:126.

     https://doi.org/10.1016/j.ajog.2021.01.020

     • PubMed
     • Google Scholar
187. Software

     1. Tarca AL

     (2024) ImmunoProteomePTB, version swh:1:rev:3052ec8cdd0e60b722e841ab6749056754a86f08

     Software Heritage.

     https://archive.softwareheritage.org/swh:1:dir:b8eaafb28e4b1dad20647984998be8db7edd7ce5;origin=https://github.com/aditarca/ImmunoProteomePTB;visit=swh:1:snp:26c45d365ff307071f4ee9baf9b61a24cedc29d1;anchor=swh:1:rev:3052ec8cdd0e60b722e841ab6749056754a86f08
188. 1. Taylor BD
     2. Holzman CB
     3. Fichorova RN
     4. Tian Y
     5. Jones NM
     6. Fu W
     7. Senagore PK

     (2013) Inflammation biomarkers in vaginal fluid and preterm delivery

     Human Reproduction 28:942–952.

     https://doi.org/10.1093/humrep/det019

     • PubMed
     • Google Scholar
189. 1. Temming LA
     2. Durst JK
     3. Tuuli MG
     4. Stout MJ
     5. Dicke JM
     6. Macones GA
     7. Cahill AG

     (2016) Universal cervical length screening: implementation and outcomes

     American Journal of Obstetrics and Gynecology 214:523.

     https://doi.org/10.1016/j.ajog.2016.02.002

     • PubMed
     • Google Scholar
190. 1. Thompson RC
     2. Ohlsson K

     (1986) Isolation, properties, and complete amino acid sequence of human secretory leukocyte protease inhibitor, a potent inhibitor of leukocyte elastase

     PNAS 83:6692–6696.

     https://doi.org/10.1073/pnas.83.18.6692

     • PubMed
     • Google Scholar
191. 1. Tiensuu H
     2. Haapalainen AM
     3. Tissarinen P
     4. Pasanen A
     5. Määttä TA
     6. Huusko JM
     7. Ohlmeier S
     8. Bergmann U
     9. Ojaniemi M
     10. Muglia LJ
     11. Hallman M
     12. Rämet M

     (2022) Human placental proteomics and exon variant studies link AAT/SERPINA1 with spontaneous preterm birth

     BMC Medicine 20:141.

     https://doi.org/10.1186/s12916-022-02339-8

     • PubMed
     • Google Scholar
192. 1. Timmons BC
     2. Fairhurst A-M
     3. Mahendroo MS

     (2009) Temporal changes in myeloid cells in the cervix during pregnancy and parturition

     Journal of Immunology 182:2700–2707.

     https://doi.org/10.4049/jimmunol.0803138

     • PubMed
     • Google Scholar
193. 1. Tribe RM

     (2015) Small peptides with a big role: antimicrobial peptides in the pregnant female reproductive tract

     American Journal of Reproductive Immunology 74:123–125.

     https://doi.org/10.1111/aji.12379

     • PubMed
     • Google Scholar
194. 1. Tricomi V
     2. Hall JE
     3. Bittar A
     4. Chambers D

     (1966)

     Arborization test for the detection of ruptured fetal membranes: clinical evaluation

     Obstetrics and Gynecology 27:275–279.

     • PubMed
     • Google Scholar
195. 1. Trinchieri G
     2. Pflanz S
     3. Kastelein RA

     (2003) The IL-12 family of heterodimeric cytokines: new players in the regulation of T cell responses

     Immunity 19:641–644.

     https://doi.org/10.1016/s1074-7613(03)00296-6

     • PubMed
     • Google Scholar
196. 1. Vadillo-Ortega F
     2. Sadowsky DW
     3. Haluska GJ
     4. Hernandez-Guerrero C
     5. Guevara-Silva R
     6. Gravett MG
     7. Novy MJ

     (2002) Identification of matrix metalloproteinase-9 in amniotic fluid and amniochorion in spontaneous labor and after experimental intrauterine infection or interleukin-1β infusion in pregnant rhesus monkeys

     American Journal of Obstetrics and Gynecology 186:128–138.

     https://doi.org/10.1067/mob.2002.118916

     • Google Scholar
197. 1. van de Veerdonk FL
     2. Netea MG

     (2010) Diversity: a hallmark of monocyte society

     Immunity 33:289–291.

     https://doi.org/10.1016/j.immuni.2010.09.007

     • Google Scholar
198. 1. Vignali DAA
     2. Kuchroo VK

     (2012) IL-12 family cytokines: immunological playmakers

     Nature Immunology 13:722–728.

     https://doi.org/10.1038/ni.2366

     • PubMed
     • Google Scholar
199. 1. Visser L
     2. van Buggenum H
     3. van der Voorn JP
     4. Heestermans LAPH
     5. Hollander KWP
     6. Wouters MGAJ
     7. de Groot CJM
     8. de Boer MA

     (2021) Maternal vascular malperfusion in spontaneous preterm birth placentas related to clinical outcome of subsequent pregnancy

     The Journal of Maternal-Fetal & Neonatal Medicine 34:2759–2764.

     https://doi.org/10.1080/14767058.2019.1670811

     • Google Scholar
200. 1. Waitzman NJ
     2. Jalali A
     3. Grosse SD

     (2021) Preterm birth lifetime costs in the United States in 2016: An update

     Seminars in Perinatology 45:151390.

     https://doi.org/10.1016/j.semperi.2021.151390

     • PubMed
     • Google Scholar
201. 1. Wakabayashi A
     2. Sawada K
     3. Nakayama M
     4. Toda A
     5. Kimoto A
     6. Mabuchi S
     7. Kinose Y
     8. Nakamura K
     9. Takahashi K
     10. Kurachi H
     11. Kimura T

     (2013) Targeting interleukin-6 receptor inhibits preterm delivery induced by inflammation

     MHR 19:718–726.

     https://doi.org/10.1093/molehr/gat057

     • Google Scholar
202. 1. Wang Y
     2. He M
     3. Zhang G
     4. Cao K
     5. Yang M
     6. Zhang H
     7. Liu H

     (2021) The immune landscape during the tumorigenesis of cervical cancer

     Cancer Medicine 10:2380–2395.

     https://doi.org/10.1002/cam4.3833

     • PubMed
     • Google Scholar
203. 1. Weber C
     2. Weber KSC
     3. Klier C
     4. Gu S
     5. Wank R
     6. Horuk R
     7. Nelson PJ

     (2001) Specialized roles of the chemokine receptors CCR1 and CCR5 in the recruitment of monocytes and TH1-like/CD45RO+T cells

     Blood 97:1144–1146.

     https://doi.org/10.1182/blood.V97.4.1144

     • Google Scholar
204. 1. Wei S-Q
     2. Fraser W
     3. Luo Z-C

     (2010) Inflammatory cytokines and spontaneous preterm birth in asymptomatic women

     Obstetrics & Gynecology 116:393–401.

     https://doi.org/10.1097/AOG.0b013e3181e6dbc0

     • Google Scholar
205. 1. Wennerholm UB
     2. Holm B
     3. Mattsby-Baltzer I
     4. Nielsen T
     5. Platz-Christensen JJ
     6. Sundell G
     7. Hagberg H

     (1998)

     Interleukin-1alpha, interleukin-6 and interleukin-8 in cervico/vaginal secretion for screening of preterm birth in twin gestation

     Acta Obstetricia et Gynecologica Scandinavica 77:508–514.

     • PubMed
     • Google Scholar
206. 1. Wenstrom K
     2. D’Alton M
     3. O’Keefe D

     (2018) Maternal–fetal medicine workforce survey: are we ready for regionalized levels of maternal care?

     American Journal of Perinatology 35:1044–1049.

     https://doi.org/10.1055/s-0038-1635093

     • Google Scholar
207. 1. Witkin SS
     2. Gravett MG
     3. Haluska GJ
     4. Novy MJ

     (1994) Induction of interleukin-1 receptor antagonist in rhesus monkeys after intraamniotic infection with group B streptococci or interleukin-1 infusion

     American Journal of Obstetrics and Gynecology 171:1668–1672.

     https://doi.org/10.1016/0002-9378(94)90419-7

     • Google Scholar
208. 1. Witkin SS
     2. Moron AF
     3. Ridenhour BJ
     4. Minis E
     5. Hatanaka A
     6. Sarmento SGP
     7. Franca MS
     8. Carvalho FHC
     9. Hamamoto TK
     10. Mattar R
     11. Sabino E
     12. Linhares IM
     13. Rudge MVC
     14. Forney LJ

     (2019) Vaginal biomarkers that predict cervical length and dominant bacteria in the vaginal microbiomes of pregnant women

     mBio 10:e02242-19.

     https://doi.org/10.1128/mBio.02242-19

     • PubMed
     • Google Scholar
209. 1. Xu Y
     2. Romero R
     3. Miller D
     4. Kadam L
     5. Mial TN
     6. Plazyo O
     7. Garcia-Flores V
     8. Hassan SS
     9. Xu Z
     10. Tarca AL
     11. Drewlo S
     12. Gomez-Lopez N

     (2016) An m1-like macrophage polarization in decidual tissue during spontaneous preterm labor that is attenuated by rosiglitazone treatment

     The Journal of Immunology 196:2476–2491.

     https://doi.org/10.4049/jimmunol.1502055

     • Google Scholar
210. 1. Yang D
     2. Biragyn A
     3. Kwak LW
     4. Oppenheim JJ

     (2002) Mammalian defensins in immunity: more than just microbicidal

     Trends in Immunology 23:291–296.

     https://doi.org/10.1016/S1471-4906(02)02246-9

     • Google Scholar
211. 1. Yarbrough VL
     2. Winkle S
     3. Herbst-Kralovetz MM

     (2015) Antimicrobial peptides in the female reproductive tract: a critical component of the mucosal immune barrier with physiological and clinical implications

     Human Reproduction Update 21:353–377.

     https://doi.org/10.1093/humupd/dmu065

     • Google Scholar
212. 1. Yilmaz E
     2. Ustunyurt E
     3. Kucukkomurcu S
     4. Budak F
     5. Ozkaya G

     (2014) Assessment of cervicovaginal vascular endothelial growth factor in predicting preterm delivery

     The Journal of Obstetrics and Gynaecology Research 40:1846–1852.

     https://doi.org/10.1111/jog.12438

     • PubMed
     • Google Scholar
213. 1. Yoo H-N
     2. Park KH
     3. Jung EY
     4. Kim YM
     5. Kook SY
     6. Jeon SJ

     (2017) Non-invasive prediction of preterm birth in women with cervical insufficiency or an asymptomatic short cervix (≤25 mm) by measurement of biomarkers in the cervicovaginal fluid

     PLOS ONE 12:e0180878.

     https://doi.org/10.1371/journal.pone.0180878

     • PubMed
     • Google Scholar
214. 1. Yoon BH
     2. Romero R
     3. Moon JB
     4. Shim S-S
     5. Kim M
     6. Kim G
     7. Jun JK

     (2001) Clinical significance of intra-amniotic inflammation in patients with preterm labor and intact membranes

     American Journal of Obstetrics and Gynecology 185:1130–1136.

     https://doi.org/10.1067/mob.2001.117680

     • Google Scholar
215. 1. Yoshimura K
     2. Hirsch E

     (2005) Effect of stimulation and antagonism of interleukin-1 signaling on preterm delivery in mice

     Journal of the Society for Gynecologic Investigation 12:533–538.

     https://doi.org/10.1016/j.jsgi.2005.06.006

     • PubMed
     • Google Scholar
216. 1. Yu H
     2. Wang X
     3. Gao H
     4. You Y
     5. Xing A

     (2015) Perinatal outcomes of pregnancies complicated by preterm premature rupture of the membranes before 34 weeks of gestation in a tertiary center in China: a retrospective review

     Bioscience Trends 9:35–41.

     https://doi.org/10.5582/bst.2014.01058

     • PubMed
     • Google Scholar