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Original Article

First trimester maternal plasma proteomic changes predictive of spontaneous moderate/late preterm delivery

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Article: 2232074 | Received 01 Jun 2022, Accepted 28 Jun 2023, Published online: 09 Jul 2023

Abstract

Objective

Identification of differentially expressed proteins (DEPs) in first trimester maternal plasma between pregnant women with a subsequent spontaneous moderate/late Preterm Delivery (sPTD) and women who delivered at term. The sPTD group consisted of women who delivered between 32°/7 and 366/7 weeks of gestation.

Methods

Isobaric tags for relative and absolute quantification (iTRAQ) coupled with LC–MS/MS was used for the analysis of five first trimester maternal plasma samples obtained from women with a subsequent moderate/late preterm sPTD and five women with term deliveries. Enzyme-linked immunosorbent assay (ELISA) was further applied in an independent cohort of 29 sPTD cases and 29 controls to verify the expression levels of selected proteins.

Results

236 DEPs, mainly linked to coagulation and complement cascade, were identified in first trimester maternal plasma obtained from the sPTD group. Decreased levels of selected proteins, namely, VCAM-1, SAA, and Talin-1, were further confirmed using ELISA, highlighting their potential as candidate predictive biomarkers for sPTD at32°/7 and 366/7 weeks of gestation.

Conclusion

First trimester maternal plasma proteomic analysis revealed protein changes associated with subsequent moderate/late preterm sPTD.

Introduction

Preterm delivery (PTD), defined as delivery before the 37th week of gestation, is a serious obstetric complication affecting 5 to 18% of all pregnancies worldwide [Citation1,Citation2]. Approximately 25% of premature deliveries are iatrogenic, i.e. due to medical indications resulting in the induction of labor, whereas the majority (75%) are spontaneous (sPTD), including sPTD with intact membranes and sPTD with premature rupture of the membranes (PPROM). Based on the gestational age at delivery, PTD is subclassified as extremely preterm (<28 weeks), very preterm (28 to 32 weeks) and moderate or late preterm (32 to 37 weeks).

SPTD has a major impact on neonatal mortality and morbidity [Citation3]. Infants who survive are particularly vulnerable for long-term health consequences, including chronic lung disease, hearing or visual impairment, and neurodevelopmental deficits that require ongoing medical care and special educational services [Citation4,Citation5].

Given the enormous personal, economic and health impact of sPTD, screening for women destined to deliver at preterm is important for pregnancy management. Ideally, women at high risk should be identified in the first trimester of pregnancy, at 11–13 weeks, resulting in their appropriate and timely monitoring and treatment.

Despite extensive efforts, only limited progress has been made in the early identification of women at risk to develop sPTD. Thus far, a predictive model that combines well‐known risk factors including maternal age, maternal BMI, racial origin, maternal behaviors, spontaneous or assisted conception and prior history of sPTD has been shown to identify only 18% of nulliparous and 38% of parous women at risk at a screen-positive rate of 10% [Citation6]. Prediction rate may increase to up to of 54.8% by combining a priori risk factors with the measurement of cervical length [Citation7]. Several biochemical markers have also been tested as early predictors of sPTD, such as PAPP-A, β-hCG, PlGF, placental protein 13 (PP13), A disintegrin, and metalloprotease 12 (ADAM12), alpha-fetoprotein (AFP), inhibin- A or activin-A, but success has been limited [Citation8].

Nowadays, mass spectrometry-based screening that allows for the simultaneous observation and identification of the abundance of changes in hundreds of proteins, is a powerful tool for biomarker discovery in various fields of medicine. Application of this high-throughput technology in the area of obstetrics is expected assist with the development of new predictive tools. The technology has previously been applied to explore candidate biomarkers associated with sPTD in samples obtained invasively such as amniotic fluid and cervical vaginal fluid [Citation9–19]. Few studies however have focused on the discovery of first trimester maternal plasma proteomic biomarkers for the early prediction of women at risk for sPTD [Citation20,Citation21].

This study aims to identify biomarkers predictive of sPTD by analyzing first trimester maternal plasma obtained from women who subsequently developed sPTD compared to full term uncomplicated pregnancies using isobaric tags for relative and absolute quantification (iTRAQ) coupled with Liquid Chromatography with tandem mass spectrometry (LC-MS-MS). The sPTD group consisted of women who experienced moderate/late sPTD, i.e. delivered between 32°/7 and 366/7 weeks of gestation, which represent more than 8% of all premature births [Citation22].

Materials and methods

Study participants and sample collection

Plasma samples for this retrospective case-control study were obtained from the maternity plasma bio-bank at the 1st Department of Obstetrics and Gynecology at Athens University School of Medicine containing stored plasma samples from pregnant women undergoing routine prenatal screening for fetal aneuploidies at 11–13 weeks of gestation. Participants were recruited between March 2018 and December 2020. During this prenatal visit, peripheral blood samples were drawn into EDTA tubes, centrifuged for 10 min at 1500 × g, after which the supernatant was aliquoted and stored at −80 °C. Maternal characteristics and medical history were recorded using a standard data collection form (Supplementary Material S1). Gestational age was determined by ultrasound measurement of fetal crown–rump length (CRL). Upon the completion of each pregnancy, outcomes became available from hospitals medical records and were recorded in the database.

Selection of samples for this study was carried out using a nested case -control design. Cases were pregnant women with a spontaneous premature delivery, before the completion of the 37th week of gestation. The control group consisted of participants with term deliveries. Cases and controls were matched for maternal age and duration of storage at −80°.

Eligible participants were pregnant women with at least one plasma aliquot available for analysis who delivered a phenotypically normal live singleton fetus. Samples from women with pregnancy related complications (e.g. gestational diabetes preeclampsia) as well as those with PPROM or signs of intra-uterine infection/inflammation at the time of admission were excluded.

During the study period, a total of 1809 plasma samples were collected from pregnant women. Τhrough the database search, we identified 63 samples coming from women who later developed sPTD. Of those, 28 were excluded from the study because of fetal chromosomal abnormality/major fetal malformations (n = 4), presence of a multiple pregnancy (n = 6), miscarriage or fetal death before 24 weeks or termination (n = 5), lost to follow-up (n = 4) or because inadequate plasma sample was available for analysis. Thirty-five (35) samples eligible for analysis were identified, including 34 from women who subsequently delivered between 32°/7 and 366/7 weeks of gestation, and one with early sPTD, i.e. with delivery before the 32nd week of gestation. This last sample was excluded to ensure increased homogeneity among the samples.

In total, 68 samples fulfilled the inclusion criteria and retrieved for analyses, 34 from women who subsequently delivered prematurely, between 32°/7 and 366/7 weeks of gestation (cases) and 34 from women with term deliveries (controls).

Initially, during the discovery stage of the study, samples from 5 women from the moderate/late sPTD group were randomly selected for analysis using iTRAQ-coupled LC-MS/MS, along with their matched controls in order to identify proteins showing significantly altered expression levels between the two groups.

During the second step of the study, the verification one, the differential expression of selected proteins identified during the discovery stage was confirmed by enzyme-linked immunosorbent assay (ELISA) in the remaining 58 samples, 29 from women who experienced moderate/late sPTD and 29 controls.

SPTD was defined by the presence of regular uterine contractions (at least two uterine contractions every 10 min for ‡30 min, as confirmed by external tocometry) in combination with cervical changes occurring prior to 37 completed weeks of gestation (366/7 weeks)that required hospitalization [Citation23].

Moderate PTD and late PTD are defined, respectively, as delivery between 32°/7 and 336/7 weeks and between 34°/7 and 366/7 weeks respectively.

A term pregnancy was defined as a delivery from 37 completed weeks to less than 42 completed weeks used to describe the optimal timing for a good outcome for the mother and baby [Citation24].

The study which was performed in accordance to the Helsinki Declaration on ethical principles for medical research involving human subjects was approved by the relevant hospital ethics committees. Prior to recruitment all women provided written informed consent to collect and use the biological samples and clinical information.

Methodologies

Discovery stage-nano LC-MS/MS analysis

First, abundant proteins were depleted and protein concentration was determined for maternal plasma samples. Proteins were then reduced and alkylated as recommended by the iTRAQ protocol. Following tryptic digestion peptide-containing solutions were separately tagged and multiplexed using iTRAQ reagents [Pierce™ TMT10plex Isobaric Label Reagent, Thermo Scientific, Waltham, MA). The tagged peptides were mixed and injected onto a Thermo Betasil C18 column (10 mm × 250 mm, 5 μm) (Thermo Scientific, Waltham, MA) for fractionation on an UltiMate 3000 HPLC system (Thermo Scientific, Waltham, MA). Each mixed sample was fractionated into 6 sections for subsequent MS analysis on an Obitrap Q Exactive™ mass spectrometer (Thermo Fisher Scientific, USA). Data were normalized by log transformation. For protein identification and quantification, the MS raw data were processed using the MaxQuant software (v1.5.8.3, Max Planck Institute of Biochemistry, Germany) and searched against HUMAN protein database (UNIPROT). Peptides/proteins identified at a FDR <1% were accepted. For protein quantification, the cutoff of >1.5 or <1.5, either up or down-regulated, with p value <.05, were considered significant.

The detailed protocol for LC MS/MS analysis is available in Supplementary Material S2.

Function enrichment analysis of DEPs

DEPs were further enriched and analyzed for known functions [biological process (BP), molecular function (MF) and cellular component (CC)] as well as KEGG pathway participation using gprofiler and WebGestalt web tools [Citation25,Citation26].

Verification stage: enzyme-linked immunosorbent assay

Enzyme-linked immunosorbent assay (ELISA) was applied to confirm the confidence of quantitative proteomics data in an independent cohort of 58 first trimester maternal plasma samples (29 from women with a subsequent moderate/late sPTD and 29 controls). Three proteins [Vascular cell adhesion protein 1 (VCAM1), Serum amyloid A-1 protein (SSA) and Talin-1] showing the most significant (lowest p values) altered expression in the sPTD group as compared to controls were selected for analysis.

All samples were analyzed in duplicates according to the manufacturer’s instructions, within 24 h of thawing, using commercially available kits for VCAM-1 [human Elisa kit (#KHT0601-Thermo Fisher Scientific, San Jose, CA, USA)], SAA [(#EHSAA1-Thermo Fisher Scientific, San Jose, CA, USA)], and Talin-1 [(#MBS904386-MyBiosource, Inc, Vancouver, British Columbia, Canada)] following the manufacturer’s protocols.

Statistical analysis

Statistical analyses were conducted in IBM SPSS Statistics 20 software (IBM Corp., Armonk, New York, USA). Pregnant women clinical characteristics and plasma protein levels between the two groups were compared using Pearson chi-square test for the evaluation of categorical variables or the Mann-Whitney U-test for continuous variables.

A two-tailed Fisher’s exact test was applied to test Gene Ontology (GO) and pathway enrichment of the DEPs against all identified proteins. The level of significance was set at p < .05.

The value of the candidate biomarkers to identify women at risk for moderate/late sPTD was evaluated by ROC curve and logistic regression analysis. Univariate and multivariate logistic regression models, adjusted for plasma protein levels, previous sPTD, maternal smoking, maternal pre-pregnancy BMI, maternal age, fetal gender and mode of conception, were used to study their independent clinical utility.

Results

Characteristics of the entire cohort

Demographic and maternal characteristics as well as delivery information of women included in the study are presented in . No significant differences were noted between the two groups.

Table 1. Maternal and neonatal characteristics of moderate/late sPTD cases and controls included in the study.

Exploratory proteomics phase-LC-MS/MS analysis

Overall, our proteomic analysis using LC MS/MS analysis of the iTRAQ labeled samples identified 236 DEPs in women who subsequently delivered preterm compared to controls (FDR < 1%). Among those, 54 demonstrated a fold change (FC) greater than 1.5 i.e. were up-regulated and 88 were decreased to less than 1.5-fold and were classified as down-regulated. No protein with significant (p < .05) altered expression, however, was detected between the 2 groups. summarizes the top 30 most significant altered proteins between cases and controls based on the lowest p-value.

Table 2. The top 30 most significant altered proteins between cases and controls based on the lowest p value.

Gene ontology and pathway analysis

GO enrichment analysis was applied for the functional characterization of DEPS. In the “molecular function” category the top five terms were peptidase regulator activity, peptidase inhibitor activity, endopeptidase inhibitor activity, endopeptidase regulator activity and glycosaminoglycan binding (Supplementary Material S3). The “biological process” category revealed that altered proteins between sPTD and the control group were engaged in humoral immune, platelet degranulation response, complement activation, immune effector process and vesicle-mediated transport. Within the “Cellular Component” category they were mainly located in extracellular region, extracellular space, blood microparticle, extracellular exosome and extracellular membrane-bounded organelle.

KEGG pathway analysis revealed that DEPs were mainly enriched in the coagulation and complement pathways, including the altered expression of Coagulation Factor F5, Prothrombin, the complement components C3, C4, H and D and Ficolin 2, suggesting that it may be a part of the initial stimuli leading to sPTD (Supplementary Material S3). Other significantly annotated pathways are as follows: Staphylococcus aureus infection, Pertussis, Cholesterol metabolism and African trypanosomiasis.

Verification stage: ELISA

Consistent with the trend of the quantitative LC MS/MS analysis, ELISA results verified the lower levels of VCAM-1, SAA, and Talin-1 in the early pregnancy maternal plasma of women who subsequently experience sPTD at 32°/7 and 366/7 weeks of gestation as compared to those with uncomplicated term deliveries (Suplementary Material S4). In order to normalize for the different units in the expression levels between the two methodologies the log2-transformed ratio samples/controls was applied.

ELISA results demonstrated that the median concentration of VCAM1 in the sPTD group was 527.27 ng/mL (IQR: 413.19–736.18) vs 621.63 ng/mL (IQR: 519.29–1030.21) in the controls, that of SAA was 24.18 μg/mL (IQR: 17.17–32.10) vs 35.59 ng/mL (IQR: 28. 14–41.80) whereas Talin −1 levels in the plasma of women who subsequently experienced sPTD was 0.26 ng/mL (IQR: 0.18–0.38) vs. 0.41 ng/mL (IQR: 0.25–0.56 26.4–54.8) in the control group ().

Figure 1. Box-plot of first trimester maternal plasma VCAM-1, SAA, and Talin-1 in 29 pregnant women who subsequently delivered preterm and 29 with term deliveries. The box represents the lower and upper quartiles, the medians are indicated by a line inside each box; the whiskers represent the 10th and 90th percentiles.

Figure 1. Box-plot of first trimester maternal plasma VCAM-1, SAA, and Talin-1 in 29 pregnant women who subsequently delivered preterm and 29 with term deliveries. The box represents the lower and upper quartiles, the medians are indicated by a line inside each box; the whiskers represent the 10th and 90th percentiles.

ROC analysis revealed that all three proteins (VCAM 1, SAA and Talin −1) have the potential to discriminate between women who will go to deliver preterm from those destine to deliver at term with AUC > 0.8 and p < .05. The ROC curves yielded the following AUCs: VCAM 1: AUC: 0.82 (95% CI: 0.715–0.928, p < .001); SAA: AUC: 0.96 (95% CI: 0.934–1.0000, p < .001) and Talin −1: AUC: 0.89 (95% CI: 0.816–0.977, p < .001) ().

Figure 2. Receiver-operating characteristics (ROC) curves showing the sensitivity and specificity of first-trimester VCAM-1, SAA, and Talin-1 as biomarkers for the early identification of women at risk for sPTL at at32°/7 to 366/7 weeks of gestation.

Figure 2. Receiver-operating characteristics (ROC) curves showing the sensitivity and specificity of first-trimester VCAM-1, SAA, and Talin-1 as biomarkers for the early identification of women at risk for sPTL at at32°/7 to 366/7 weeks of gestation.

Univariate logistic regression analysis demonstrated that plasma levels of VCAM 1, SAA and Talin −1 are significant early predictors of sPTD at 32°/7 to 366/7 weeks of gestation ().Furthermore, the multivariable regression model, revealed that VCAM 1 (p = .001) and Talin −1 (p < .001) can significantly predict subsequent sPTD independently of the confounding factors tested (previous sPTD, maternal smoking, maternal pre-pregnancy BMI, maternal age, fetal gender and mode of conception) whereas SAA is marginally not significant (p = .07).

Table 3. Logistic regression analysis for the prediction of sPTD patients according to plasma protein levels.

Discussion

In the present study, first trimester maternal plasma proteome was examined in relation to moderate/late sPTD at 11–13 weeks of gestation using the powerful quantitative proteomic technique of iTRAQ labeling coupled with LC-MS/MS mass spectrometry.

Compared to first trimester plasma samples obtained from women who delivered at term, proteomic analysis revealed changes in concentration of 236 proteins. Although these alterations did not reach the criterion of the very low p-value of significance (p < .05), they represent candidate biomarkers for moderate/late sPTD and may provide a useful basis for the development of a predictive test to assist clinicians in estimating patient-specific risks.

Consistent with existing literature, complement factor C3 was down regulated in the first trimester maternal plasma obtained from women who later experienced sPTD as compared to their matched controls delivering at term [Citation20,Citation27].

Lower levels of the coagulation factor F5, known to be involved in the formation of fibrin clot, were also noted in our study. In contrast, Lee et al. reported higher levels of coagulation F5 in plasma samples of women with PTL at 24–32 week [Citation28]. It is noteworthy that several F5 have been are considered as risk factors for preterm birth [Citation29].

Furthermore, Ficolin 2 was found up regulated in moderate/late sPTD cases. Ficolin 2 is involved in the clearance of pathogens and apoptotic/necrotic cells either by activating the lectin complement pathway either directly or via phagocytosis [Citation30]. Increased concentrations of Ficolin 2 have been previously identified in the third trimester maternal plasma in women with preeclampsia. However, up until today, no reports exist regarding the role of this molecule in the pathogenesis of other pregnancy complications [Citation30,Citation31].

Our findings revealed that S100-A9, known as calgranulin B, showed a three-fold increased expression level in the first trimester maternal plasma of women at greatest risk for sPTD. S100-A9 is a calcium-binding protein that modulates inflammatory and immune responses [Citation32]. Elevated levels of S100-A9 have been identified in amniotic fluid, cervical fluid as well as maternal plasma as a diagnostic marker for intra-amniotic infection [Citation9,Citation32,Citation33]. In contrast, Lee et al. reported lower levels of S100-A9 in the plasma women who delivered prematurely within 21 days of sampling [Citation28].

An important observation that merits attention is the down regulation of Talin-1, SAA, and VCAM-1 in the first trimester maternal plasma of women who subsequently developed sPTD which was demonstrated using both LC MS/MS proteomic analysis and ELISA. However, discrepancies were noted in the significance values (p value) of these alterations. This finding may be explained by the limited number of samples analyzed by LC-MSMS. Results were verified in an independent extended cohort that confirmed a significant down regulation of VCAM1, SAA, and Talin-1 in sPTD cases as compared to controls. Following statistical analysis, the AUC values obtained when Talin-1, SAA, and VCAM-1 were used as single biomarkers were >85%. Logistic regression analysis highlighted their potential of VCAM1 and Talin-1 as early predictors of sPTD independent of well-known risk factors (previous sPTD, maternal smoking, maternal pre-pregnancy BMI, maternal age, fetal gender and mode of conception).

VCAM-1, originally identified as a cell adhesion molecule, is implicated in the regulation of an inflammatory response and the trans-membrane migration of leukocytes to the sites of inflammation. VCAM-1 expression is stimulated by IL-1, IL-6, reactive oxygen species (ROS), high glucose concentration, and TNF-a [Citation34,Citation35]. Consequently, increased concentrations of VCAM-1 have been considered as early signs indicative of a chronic inflammatory disease [Citation34]. In the context of pregnancy related complications, a positive association between serum levels of VCAM-1 and preeclampsia, small for gestational age (SGA) and IUGR fetuses, has been reported [Citation36–38]. Still, inconsistent results exist regarding maternal peripheral blood levels of VCAM-1 and premature delivery [Citation35,Citation36,Citation39–41]. This is could be attributed to gestational age at sample collection. Indicatively, Chen et al. using samples obtained at 16 and 30 weeks of gestation reported higher serum levels of VCAM-1 in women with PTD compared to those with a normal term pregnancy. On the other hand, Nikolina Docheva et al. upon diagnosis, noted lower concentrations of VCAM-1 [Citation36].

SAA, originally identified as a component of amyloid places in amyloid A (AA)–type systemic amyloidosis is synthesized in the liver as well as in the leukocytes, adipocytes, synoviocytes, tumor cells and trophoblasts. Several studies have demonstrated its role in cell proliferation, the initiation of immune responses, phagocytosis, the clearance of apoptotic cells and lipid metabolism [Citation42]. During pregnancy, SAA has been associated with fetal development and placenta homeostasis. In vitro studies aiming to evaluate the effects of SAA on cell invasion and differentiation showed that SAA administration decreased the expression of bHCG and induced invasion in a TLR4-dependent manner indicating a significant role of SAA in placentation and early fetal development

To our knowledge this is the first time that Talin1 is reported in relation to moderate/late sPTD. Talin1 is a cytoplasmic adapter protein, known to connect cells to the extracellular matrix. As an activator of integrins, talin 1 is associated with cell migration, focal adhesion formation and tumerogenesis [Citation43–46]. Altered expression of Talin 1 was found in the endometrial carcinoma, colorectal cancer, prostate cancer, breast cancer, liver and ovarian cancer. Recently Talin-1 has been implicated the development of endometriosis and in embryo implantation by facilitating endometrial cell adhesion [Citation47,Citation48].

The main advantage of the study lies with the use of a sensitive method for relative protein quantitation followed by verification of proteomic data obtained with the use of ELISA. In addition, sample collection and handling were performed using a standardized protocol. Finally, a homogenous group of well characterized samples collected by scientists with great experience in the field of maternal and fetal medicine grants additional strengths.

There are several limitations to the study design that uses a cohort with uncomplicated pregnancies who later developed preterm labor compared to those who delivered at term, matched for maternal age. These limitations include:1. Selection bias: The study may only include women who were willing to participate, which could lead to a biased sample of patients. Additionally, selection criteria that exclude certain groups of women could also affect the findings. 2. Confounding variables: There may be other factors that significantly affect the outcome of the study, such as socioeconomic status or lifestyle choices, that were not accounted for in the study design.

Other potential limitations are associated with a small study size, the retrospective design and the use of frozen samples. In addition, elevated costs associated with MS based proteomics results in studies, including ours, to be almost underpowered, limiting their ability for biomarker discovery.

Finally, it is worthy of discussion whether candidate biomarkers identified in the present study have the potential to be used for the detection of very preterm delivery (<32 weeks of gestation), which is the most common cause of perinatal mortality. Therefore, careful consideration should be given to these limitations when interpreting results and drawing conclusions.

Conclusion

Overall, application of LC MS proteomic analysis of first trimester maternal plasma samples revealed a proteomic profile associated with the subsequent development of moderate/late sPTD. Novel findings, namely the down-regulation of VCAM 1, SAA and Talin −1, may facilitate the development of a predictive test of clinical significance for sPTD as well as the design of therapeutics to extend pregnancy to term. Nevertheless, since the limitations of the study can reduce the overall validity and generalizability of the candidate biomarkers, future prospective studies with a larger number of unselected participants are necessary to validate the initial findings and assess their clinical utility.

Ethics approval

Please refer to the “Materials and Methods” section.

Consent form

Please refer to the “Materials and Methods” section.

Authors’ contributions

DM: experimental work, data analysis, literature search and manuscript preparation, MT: sample and data collection, sample selection, literature search and manuscript preparation, GL and MA: bioinformatic and statistical analyses, NP: sample selection, literature search and manuscript critical review. JTS: sample selection, literature search and manuscript critical review, JD: sample and data collection, sample selection, and critical review AK: conceived and designed the experiments and provided critical review. All authors read and approved the final version of the manuscript.

Supplemental material

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Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Please also refer to the “Materials and Methods” section.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

No funding received.

References

  • Vogel JP, Chawanpaiboon S, Moller AB, et al. The global epidemiology of preterm birth. Best Pract Res Clin Obstet Gynaecol. 2018;52:3–12. doi: 10.1016/j.bpobgyn.2018.04.003.
  • Di Renzo GC, Cabero Roura L, Facchinetti F, et al. Preterm labor and birth management: recommendations from the European Association of Perinatal Medicine. J Matern Fetal Neonatal Med. 2017;30(17):2011–2030.
  • Goldenberg RL, Culhane JF, Iams JD, et al. Epidemiology and causes of preterm birth. Lancet. 2008;371(9606):75–84. doi: 10.1016/S0140-6736(08)60074-4.
  • Norwitz ER, Robinson JN. A systematic approach to the management of preterm labor. Semin Perinatol. 2001;25(4):223–235. doi: 10.1053/sper.2001.26417.
  • Stephens BE, Vohr BR. Neurodevelopmental outcome of the premature infant. Pediatr Clin North Am. 2009;56(3):631–646, Table of Contents. doi: 10.1016/j.pcl.2009.03.005.
  • Beta J, Akolekar R, Ventura W, et al. Prediction of spontaneous preterm delivery from maternal factors, obstetric history and placental perfusion and function at 11-13 weeks. Prenat Diagn. 2011;31(1):75–83. doi: 10.1002/pd.2662.
  • Greco E, Gupta R, Syngelaki A, et al. First-trimester screening for spontaneous preterm delivery with maternal characteristics and cervical length. Fetal Diagn Ther. 2012;31(3):154–161. doi: 10.1159/000335686.
  • Vogel I, Thorsen P, Curry A, et al. Biomarkers for the prediction of preterm delivery. Acta Obstet Gynecol Scand. 2005;84(6):516–525. doi: 10.1111/j.0001-6349.2005.00771.x.
  • Ruetschi U, Rosen A, Karlsson G, et al. Proteomic analysis using protein chips to detect biomarkers in cervical and amniotic fluid in women with intra-amniotic inflammation. J Proteome Res. 2005;4(6):2236–2242. doi: 10.1021/pr050139e.
  • Buhimschi IA, Christner R, Buhimschi CS. Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation. BJOG. 2005;112(2):173–181. doi: 10.1111/j.1471-0528.2004.00340.x.
  • Buhimschi IA, Zhao G, Rosenberg VA, et al. Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth. PLoS One. 2008;3(4):e2049. doi: 10.1371/journal.pone.0002049.
  • Cobo T, Palacio M, Navarro-Sastre A, et al. Predictive value of combined amniotic fluid proteomic biomarkers and interleukin-6 in preterm labor with intact membranes. Am J Obstet Gynecol. 2009;200(5):499 e1–499.e6. doi: 10.1016/j.ajog.2008.12.036.
  • Fotopoulou C, Kyeyamwa S, Linder M, et al. Proteomic analysis of midtrimester amniotic fluid to identify novel biomarkers for preterm delivery. J Matern Fetal Neonatal Med. 2012;25(12):2488–2493.
  • Pereira L, Reddy AP, Jacob T, et al. Identification of novel protein biomarkers of preterm birth in human cervical-vaginal fluid. J Proteome Res. 2007;6(4):1269–1276. doi: 10.1021/pr0605421.
  • Shah SJ, Yu KH, Sangar V, et al. Identification and quantification of preterm birth biomarkers in human cervicovaginal fluid by liquid chromatography/tandem mass spectrometry. J Proteome Res. 2009;8(5):2407–2417. doi: 10.1021/pr8010342.
  • Hong S, Lee JE, Kim YM, et al. Identifying potential biomarkers related to pre-term delivery by proteomic analysis of amniotic fluid. Sci Rep. 2020;10(1):19648. doi: 10.1038/s41598-020-76748-1.
  • Liong S, Di Quinzio MK, Fleming G, et al. Prediction of spontaneous preterm labour in at-risk pregnant women. Reproduction. 2013;146(4):335–345. doi: 10.1530/REP-13-0175.
  • Di Quinzio MK, Georgiou HM, Holdsworth-Carson SJ, et al. Proteomic analysis of human cervico-vaginal fluid displays differential protein expression in association with labor onset at term. J Proteome Res. 2008;7(5):1916–1921. doi: 10.1021/pr7006413.
  • Lynch AM, Wagner BD, Deterding RR, et al. The relationship of circulating proteins in early pregnancy with preterm birth. Am J Obstet Gynecol. 2016;214(4):517 e1–517 e8. doi: 10.1016/j.ajog.2015.11.001.
  • D’Silva AM, Hyett JA, Coorssen JR. Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth. J Proteomics. 2018;178:31–42. doi: 10.1016/j.jprot.2018.02.002.
  • Cantonwine DE, Zhang Z, Rosenblatt K, et al. Evaluation of proteomic biomarkers associated with circulating microparticles as an effective means to stratify the risk of spontaneous preterm birth. Am J Obstet Gynecol. 2016;214(5):631 e1–631 e11.
  • Frey HA, Klebanoff MA. The epidemiology, etiology, and costs of preterm birth. Semin Fetal Neonatal Med. 2016;21(2):68–73. doi: 10.1016/j.siny.2015.12.011.
  • Tsiartas P, Holst RM, Wennerholm UB, et al. Prediction of spontaneous preterm delivery in women with threatened preterm labour: a prospective cohort study of multiple proteins in maternal serum. BJOG. 2012;119(7):866–873. doi: 10.1111/j.1471-0528.2012.03328.x.
  • ACOG committee opinion no 579: definition of term pregnancy. Obstet Gynecol. 2013;122(5):1139–1140.
  • Raudvere U, Kolberg L, Kuzmin I, et al. g: profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 2019;47(W1):W191–W198. doi: 10.1093/nar/gkz369.
  • Wang J, Vasaikar S, Shi Z, et al. WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit. Nucleic Acids Res. 2017;45(W1):W130–W137. doi: 10.1093/nar/gkx356.
  • Suski M, Bokiniec R, Szwarc-Duma M, et al. Plasma proteome changes in cord blood samples from preterm infants. J Perinatol. 2018;38(9):1182–1189. doi: 10.1038/s41372-018-0150-7.
  • Lee JE, Park KH, Kim HJ, et al. Proteomic identification of novel plasma biomarkers associated with spontaneous preterm birth in women with preterm labor without infection/inflammation. PLoS One. 2021;16(10):e0259265. doi: 10.1371/journal.pone.0259265.
  • Hiltunen LM, Laivuori H, Rautanen A, et al. Factor V Leiden as a risk factor for preterm birth–a population-based nested case-control study. J Thromb Haemost. 2011;9(1):71–78. doi: 10.1111/j.1538-7836.2010.04104.x.
  • Halmos A, Rigo J Jr, Szijarto J, et al. Circulating ficolin-2 and ficolin-3 in normal pregnancy and pre-eclampsia. Clin Exp Immunol. 2012;169(1):49–56. doi: 10.1111/j.1365-2249.2012.04590.x.
  • Wang CC, Yim KW, Poon TC, et al. Innate immune response by ficolin binding in apoptotic placenta is associated with the clinical syndrome of preeclampsia. Clin Chem. 2007;53(1):42–52. doi: 10.1373/clinchem.2007.074401.
  • Gomez-Lopez N, StLouis D, Lehr MA, et al. Immune cells in term and preterm labor. Cell Mol Immunol. 2014;11(6):571–581. doi: 10.1038/cmi.2014.46.
  • Klein LL, Jonscher KR, Heerwagen MJ, et al. Shotgun proteomic analysis of vaginal fluid from women in late pregnancy. Reprod Sci. 2008;15(3):263–273. doi: 10.1177/1933719107311189.
  • Meigs JB, Hu FB, Rifai N, et al. Biomarkers of endothelial dysfunction and risk of type 2 diabetes mellitus. JAMA. 2004;291(16):1978–1986. doi: 10.1001/jama.291.16.1978.
  • Bartha JL, Fernandez-Deudero A, Bugatto F, et al. Inflammation and cardiovascular risk in women with preterm labor. J Womens Health. 2012;21(6):643–648. doi: 10.1089/jwh.2011.3013.
  • Docheva N, Romero R, Chaemsaithong P, et al. The profiles of soluble adhesion molecules in the “great obstetrical syndromes.” J Matern Fetal Neonatal Med. 2019;32(13):2113–2136.
  • Coata G, Pennacchi L, Bini V, et al. Soluble adhesion molecules: marker of pre-eclampsia and intrauterine growth restriction. J Matern Fetal Neonatal Med. 2002;12(1):28–34.
  • Vrachnis N, Zygouris D, Vrachnis D, et al. Perinatal inflammation: could partial blocking of cell adhesion molecule function be a solution? Children. 2021;8(5):380. doi: 10.3390/children8050380.
  • Huang MT, Larbi KY, Scheiermann C, et al. ICAM-2 mediates neutrophil transmigration in vivo: evidence for stimulus specificity and a role in PECAM-1-independent transmigration. Blood. 2006;107(12):4721–4727. doi: 10.1182/blood-2005-11-4683.
  • Woodfin A, Voisin MB, Nourshargh S. PECAM-1: a multi-functional molecule in inflammation and vascular biology. Arterioscler Thromb Vasc Biol. 2007;27(12):2514–2523. doi: 10.1161/ATVBAHA.107.151456.
  • Chen X, Scholl TO. Maternal biomarkers of endothelial dysfunction and preterm delivery. PLoS One. 2014;9(1):e85716. doi: 10.1371/journal.pone.0085716.
  • Sandri S, Urban Borbely A, Fernandes I, et al. Serum amyloid a in the placenta and its role in trophoblast invasion. PLoS One. 2014;9(3):e90881. doi: 10.1371/journal.pone.0090881.
  • Kopp PM, Bate N, Hansen TM, et al. Studies on the morphology and spreading of human endothelial cells define key inter- and intramolecular interactions for talin1. Eur J Cell Biol. 2010;89(9):661–673. doi: 10.1016/j.ejcb.2010.05.003.
  • Zhang X, Jiang G, Cai Y, et al. Talin depletion reveals independence of initial cell spreading from integrin activation and traction. Nat Cell Biol. 2008;10(9):1062–1068. doi: 10.1038/ncb1765.
  • Slater M, Cooper M, Murphy CR. The cytoskeletal proteins alpha-actinin, ezrin, and talin are de-expressed in endometriosis and endometrioid carcinoma compared with normal uterine epithelium. Appl Immunohistochem Mol Morphol. 2007;15(2):170–174. doi: 10.1097/01.pai.0000194762.78889.26.
  • Shen Y, Qin A. Regulation of embryonic signal on Talin1 in mouse endometrium. Reprod Sci. 2019;26(9):1277–1286. doi: 10.1177/1933719118815584.
  • Tang X, Li Q, Li L, et al. Expression of talin-1 in endometriosis and its possible role in pathogenesis. Reprod Biol Endocrinol. 2021;19(1):42. doi: 10.1186/s12958-021-00725-0.
  • Chen S, Liu B, Li J, et al. Talin1 regulates endometrial adhesive capacity through the ras signaling pathway. Life Sci. 2021;274:119332. doi: 10.1016/j.lfs.2021.119332.