BACKGROUND: Despite much research, advances in early prediction of spontaneous preterm birth (sPTB) has been slow. The evolving field of circulating microparticle (CMP) biology may identify novel blood-based, and clinically useful, biomarkers. OBJECTIVE: To test the ability of a previously identified, 7-marker set of CMP-derived proteins from the first trimester of pregnancy, in the form of an in vitro diagnostic multivariate index assay (IVDMIA), to stratify pregnant patients according to their risk for sPTB. STUDY DESIGN: We employed a previously validated set of CMP protein biomarkers, utilizing mass spectrometry assays and a nested case- control design in a subset of participants from the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (nuMoM2b). We evaluated these biomarkers in the form of an IVDMIA to predict risk for sPTB at different gestational ages. Plasma samples collected at 9- to 13-weeks' gestation were analyzed. The IVDMIA assigned subjects to 1 of 3 sPTB risk categories: low risk (LR), moderate risk (MR), or high risk (HR). Independent validation on a set-aside set confirmed the IVDMIA's performance in risk stratification. RESULTS: Samples from 400 participants from the nuMoM2b cohort were used for the study; of these, 160 delivered<37 weeks and 240 delivered at term. Through Monte Carlo simulation in which the validation results were adjusted based on actual weekly sPTB incidence rates in the nuMoM2b cohort, the IVDMIA stratifications demonstrated statistically significant differences among the risk groups in time-to-event (birth) analysis (P<.0001). The incidence- rate adjusted cumulative risks of sPTB at <= 32 weeks' gestation were 0.4%, 1.6%, and 7.5%, respectively for the LR, M R, and HR groups, respectively. Compared to the LR group, the corresponding risk ratios of the IVDMIA assigned MR and HR group were 4.25 (95% confidence interval [CI] 2.2-7.9) and 19.92 (95% CI 10.4-37.4), respectively. CONCLUSION: A first trimester CMP protein biomarker panel can be used to stratify risk for sPTB at different gestational ages. Such a multitiered stratification tool could be used to assess risk early in pregnancy to enable timely clinical management and interventions, and, ultimately, to enable the development of tailored care pathways for sPTB prevention.

Placenta accreta spectrum (PAS) is characterized by abnormal attachment of the placenta to the uterus, and attempts at placental delivery can lead to catastrophic maternal hemorrhage and death. Multidisciplinary delivery planning can significantly improve outcomes; however, current diagnostics are lacking as approximately half of pregnancies with PAS are undiagnosed prior to delivery. This is a nested case–control study of 35 cases and 70 controls with the primary objective of identifying circulating microparticle (CMP) protein panels that identify pregnancies complicated by PAS. Size exclusion chromatography and liquid chromatography with tandem mass spectrometry were used for CMP protein isolation and identification, respectively. A two-step iterative workflow was used to establish putative panels. Using plasma sampled at a median of 26 weeks’ gestation, five CMP proteins distinguished PAS from controls with a mean area under the curve (AUC) of 0.83. For a separate sample taken at a median of 35 weeks’ gestation, the mean AUC was 0.78. In the second trimester, canonical pathway analyses demonstrate over-representation of processes related to iron homeostasis and erythropoietin signaling. In the third trimester, these analyses revealed abnormal immune function. CMP proteins classify PAS well prior to delivery and have potential to significantly reduce maternal morbidity and mortality.

We hypothesize that first trimester circulating micro particle (CMP) proteins will define preeclampsia risk while identifying clusters of disease subtypes among cases. We performed a nested case–control analysis among women with and without preeclampsia. Cases diagnosed < 34 weeks’ gestation were matched to controls. Plasma CMPs were isolated via size exclusion chromatography and analyzed using global proteome profiling based on HRAM mass spectrometry. Logistic models then determined feature selection with best performing models determined by cross-validation. K-means clustering examined cases for phenotypic subtypes and biological pathway enrichment was examined. Our results indicated that the proteins distinguishing cases from controls were enriched in biological pathways involved in blood coagulation, hemostasis and tissue repair. A panel consisting of C1RL, GP1BA, VTNC, and ZA2G demonstrated the best distinguishing performance (AUC of 0.79). Among the cases of preeclampsia, two phenotypic sub clusters distinguished cases; one enriched for platelet degranulation and blood coagulation pathways and the other for complement and immune response-associated pathways (corrected p < 0.001). Significantly, the second of the two clusters demonstrated lower gestational age at delivery ( p = 0.049), increased protein excretion ( p = 0.01), more extreme laboratory derangement ( p < 0.0001) and marginally increased diastolic pressure ( p = 0.09). We conclude that CMP-associated proteins at 12 weeks’ gestation predict the overall risk of developing early preeclampsia and indicate distinct subtypes of pathophysiology and clinical morbidity.

BACKGROUND: We have previously shown that protein biomarkers associated with circulating microparticles proteins (CMPs) obtained at the end of the first trimester may detect physiologic changes in maternal-fetal interaction such that the risk of spontaneous preterm delivery <= 35 weeks can be stratified. OBJECTIVES: We present here a study extension and validation of the CMP protein multiplex concept using a larger sample set from a multicenter population that allows for model derivation in a training set and characterization in a separate testing set. MATERIALS AND METHODS: Ethylenediaminetetraacetic acid (EDTA) plasma was obtained from 3 established biobanks (Seattle, Boston, and Pittsburgh). Samples were from patients at a median of 10-12 weeks' gestation, and the CMPs were isolated via size-exclusion chromatography followed by protein identification via targeted protein analysis using liquid chromatography-multiple reaction monitoring-mass (LC-MRM) spectrometry. A total of 87 women delivered at <= 35 weeks, and 174 women who delivered at term were matched by maternal age (+/- 2 years) and gestational age at sample draw (+/- 2 weeks). From our prior work, the CMP protein multiplex comprising F13A, FBLN1, IC1, ITIH2, and LCAT was selected for validation. RESULTS: For delivery at <= 35 weeks, the receiver operating characteristic (ROC) curve for a panel of CMP proteins (F13A, FBLN1, IC1, ITIH2, and LCAT) revealed an associated area under the ROC curve (AUC) of 0.74 (95% CI, 0.63-0.81). A separate panel of markers (IC1, LCAT, TRFE, and ITIH4), which stratified risk among mothers with a parity of 0, showed an AUC of 0.77 (95% CI, 0.61-0.90). CONCLUSION: We have identified a set of CMP proteins that provide, at 10-12 weeks gestation, a clinically useful AUC in an independent test population. Furthermore, we determined that parity is pertinent to the diagnostic testing performance of the biomarkers for risk stratification.

We hypothesize that proteins associated with circulating extracellular vesicles (EVs) obtained in the late second trimester will differ in pregnancies that go on to experience spontaneous preterm birth (sPTB) <35 weeks compared to those who deliver at term. EDTA plasma samples were obtained at 24-28 weeks gestation as part of a prospective birth cohort. All pregnancy outcomes were validated by two independent physician reviewers. Twenty-five singleton cases of sPTB were matched by maternal age, race and gestational age at sampling (± 2weeks) with 50 uncomplicated term deliveries. EVs were isolated via size-exclusion chromatography and targeted protein analysis using multiple reaction monitoring-mass spectrometry. To identify candidate proteins we used bootstrap receiver-operator curve (ROC) analysis with label permutation to estimate the false discovery rate (FDR). Candidate proteins were also interrogated with elastic net regularized regression analysis (α=0.3). Robust markers identified by both techniques were further evaluated for their biological relevance and multivariate performance. Of the 132 proteins evaluated, 12 demonstrated robust classification of sPTB by ROC analysis with a FDR<20% (Table 1). Of these markers, 7 were concurrently identified by regularized regression. Ontological analysis identified protein function linked to biological processes of inflammation, wound healing, and regulators of inflammation (Table 1). Linear models of sPTB using multiplexed panels of the candidate biomarkers was not as informative as single marker analysis. We have identified functional EV proteins with associated biological processes at 24-28 weeks among women who go on to deliver spontaneously <35 weeks. Many of these proteins are unique compared to our prior published work at 10-12 weeks, suggesting evolving gestational age specific EV profiles and the potential to further identify women vulnerable to sPTB in a preclinical period.

The evolving field of extracellular vesicle (EV) biology has developed rapidly particularly with regard to understanding the complications of pregnancy. To date, there have been fewer reports of the longitudinal changes of EV proteomics over the course of gestation. Here, we classify the kinetics of EV proteomics with gestational progress over the first two trimesters. We collected 150 EDTA plasma samples at two time points (median 11.3 and median 25.3 weeks gestation; N=75 at each time point) as part of a prospectively collected birth cohort. EVs were isolated via size-exclusion chromatography and were analyzed using targeted protein analysis by multiple reaction monitoring mass spectrometry. Least squares regressions on normalized protein concentrations, as the dependent variable, were run for each protein separately at both median 11 and 25 weeks with gestational age as the dependent variable. Gestational age was introduced both as a linear and quadratic transformation to test for possible non-linear effects on EV concentration. We identified three patterns of EV proteomic behavior with progressive gestational age: 1) there were significant linear changes in protein concentrations. 2) there were 74 proteins, out of 130, that showed a significant non-linear protein concentration change across the first and second trimester (as an example see LG3BP in Figure 1) and 3) we found that 27 proteins out of 130 exhibited no significant change with gestational age and remained at a fixed concentration across gestation. The ten proteins with the lowest p-values in each category are described in Table 1. EVs in the maternal circulation display three distinct kinetic characteristics with regard to gestational age. The majority increase either in a linear or non-linear fashion. However, a distinct subset of proteins remain at a constant concentration with progressing gestation. These differences possibly reflect differences in their origins as placental vs. maternal.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

We have previously suggested that circulating microparticle-derived proteins (CMPs) obtained at the end of the first trimester carry markers for physiologic changes in maternal-fetal interactions such that the risk of spontaneous preterm delivery <35 weeks can be stratified. We present here a validation of the CMP protein multi-marker concept in a multicenter population with additional investigation of the testing characteristics by body mass index (BMI), parity, and fetal sex. EDTA plasma was obtained from three established biobanks (Seattle, Boston and Pittsburgh). Samples were from a median 12 weeks gestation and CMPs were isolated via size-exclusion chromatography with protein identification via targeted protein analysis using multiple reaction monitoring-mass spectrometry. The samples evaluated do not overlap with our prior set. 53 women delivered <35 weeks and 106 were matched by race, maternal age (± 2years), parity and gestational age at sample draw (± 2weeks). From our prior work, the CMP protein multi-marker panel, F13A, FBLN1, IC1, ITIH1 and LCAT, was selected for validation Figure 1 presents the ROC for the multiplexed panel with an associated area under the curve (AUC) of 0.73 (95% CI: 0.56-0.91). Test performance did not change with BMI. Figure 2 demonstrates that test performance was increased for female (AUC .79) versus male fetuses (AUC .64) and for nuliparious (AUC .78) as opposed to multiparious (AUC .66). We have identified a set of CMP proteins that, at the median of 12 weeks gestation, provide clinically useful biomarkers in a separate, multicenter population. Furthermore, we determined that maternal and fetal characteristics are pertinent to understanding overall testing performance. Additional studies in additional populations to further delineate test utility are ongoing.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Extracellular vesicles (EVs) provide a novel and increasingly useful source of proteomic information separate from protein analysis in plasma alone. We hypothesize that EV protein profiling and analysis will provide a unique group of protein biomarkers for spontaneous preterm births compared to direct analysis of free plasma proteins. Twenty-five sPTB and 50 term EDTA plasma specimens were obtained at a median of 25 weeks gestation and matched by maternal age, race and gestational age at sampling. Vesicles were isolated from one aliquot via size exclusion chromatography (SEC) and the other was left as plasma (PPS). Both samples were analyzed by multiple reaction monitoring mass spectrometry for a targeted set of proteins. Data from the SEC and PPS samples was analyzed with a bootstrap receiver-operator curve (ROC) analysis that was performed with label permutation for a false discovery rate <20% for the identification of sPTB. The permutation test of Venkatraman was used to compare the significance of the area under the curve (AUC) in the SEC and PPS fractions for each of the top paired candidate markers. Of the 132 proteins evaluated, the median relative concentrations in the plasma versus EV samples for each protein are presented in the figure which illustrate little similarity between the fractions. The top ten bootstrapped AUCs, with regard to the prediction of sPTB, are presented in Table 1. The AUCs among the SEC were significantly higher than the corresponding PPS with no overlap in the top performing proteins between the two fractions. Among the top single marker predictors of sPTB from both EV and plasma proteins, the EV protein markers tended to display significantly better ROC characteristics. Circulating EV associated proteins represent a source of biomarker information that is distinct from proteins derived directly from the plasma.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

BACKGROUND: The analysis of circulating microparticles in pregnancy is of revolutionary potential because it represents an in vivo biopsy of active gestational tissues.OBJECTIVE: We hypothesized that circulating microparticle signaling will differ in pregnancies that experience spontaneous preterm birth from those delivering at term and that these differences will be evident many weeks in advance of clinical presentation.STUDY DESIGN: Utilizing plasma specimens obtained between 10 and 12 weeks' gestation as part of a prospectively collected birth cohort in which pregnancy outcomes are independently validated by 2 boardcertified maternal-fetal medicine physicians, 25 singleton cases of spontaneous preterm birth <= 34 weeks were matched by maternal age, race, and gestational age of sampling (+/- 2 weeks) with 50 uncomplicated term deliveries. Circulating microparticles from these first-trimester specimens were isolated and analyzed by multiple reaction monitoring mass spectrometry for potential protein biomarkers following previous studies. Markers with robust univariate performance in correlating spontaneous preterm birth were further evaluated for their biological relevance via a combined functional profiling/pathway analysis and for multivariate performance.RESULTS: Among the 132 proteins evaluated, 62 demonstrated robust power of detecting spontaneous preterm birth in a bootstrap receiveroperating characteristic curve analysis at a false discovery rate of < 20% estimated via label permutation. Differential dependency network analysis identified spontaneous preterm birth-associated coexpression patterns linked to biological processes of inflammation, wound healing, and the coagulation cascade. Linear modeling of spontaneous preterm birth using a multiplex of the candidate biomarkers with a fixed sensitivity of 80% exhibited a specificity of 83% with median area under the curve of 0.89. These results indicate a strong potential of multivariate model development for informative risk stratification.CONCLUSION: This project has identified functional proteomic factors with associated biological processes that are already unique in their expression profiles at 10-12 weeks among women who go on to deliver spontaneously <= 34 weeks. These changes, with further validation, will allow the stratification of patients at risk of spontaneous preterm birth before clinical presentation.

The analysis of circulating microparticles (CMPs) in pregnancy is of revolutionary potential as it represents an in vivo 'biopsy' of active gestational tissues. We hypothesize that CMP signaling will differ in pregnancies that experience spontaneous preterm birth (SPTB) from those delivering at term and that these differences will be evident many weeks in advance of clinical presentation. Utilizing plasma specimens obtained between 10-12 weeks gestation as part of a prospectively collected birth cohort where pregnancy outcomes are independently validated by two board certified MFM physicians, 25 singleton cases of SPTB prior to 34 weeks were matched by maternal age, race, and gestational age of sampling (+/- 2 weeks) to 50 uncomplicated term deliveries. CMPs from these first trimester specimens were isolated and analyzed by multiple reaction monitoring mass spectrometry for potential protein biomarkers selected from previous studies. Markers with robust univariate performance in correlating SPTB were further evaluated for their biological relevance via a combined functional profiling/pathway analysis. Among the 132 proteins evaluated, 62 demonstrated robust power of detecting SPTB in bootstrap receiver-operating characteristic curve analysis at a false discovery rate of < 20% estimated via label permutation. Differential dependency network analysis identified SPTB-associated co-expression patterns linked to biological processes of inflammation, wound healing, the coagulation cascade, and steroid metabolism. An initial linear model of SPTB using 2 of the candidate biomarkers had a sensitivity of 80% (20/25) and specificity of 78% (39/50) indicating strong potential of multivariate model development. This project has identified functional proteomic factors with associated biological processes that are already unique in their expression profiles at 10-12 weeks among women who go on to deliver spontaneously <34 weeks. These changes, with further validation, will allow the stratification of patients at risk of SPTB before clinical presentation.