Immunosequencing and Profiling of T Cells at the Maternal-Fetal Interface of Women with Preterm Labor and Chronic Chorioamnionitis

T cells are implicated in the pathophysiology of preterm labor and birth, the leading cause of neonatal morbidity and mortality worldwide. Specifically, maternal decidual T cells infiltrate the chorioamniotic membranes in chronic chorioamnionitis (CCA), a placental lesion considered to reflect maternal anti-fetal rejection, leading to preterm labor and birth. However, the phenotype and TCR repertoire of decidual T cells in women with preterm labor and CCA have not been investigated. In this study, we used phenotyping, TCR sequencing, and functional assays to elucidate the molecular characteristics and Ag specificity of T cells infiltrating the chorioamniotic membranes in women with CCA who underwent term or preterm labor. Phenotyping indicated distinct enrichment of human decidual effector memory T cell subsets in cases of preterm labor with CCA without altered regulatory T cell proportions. TCR sequencing revealed that the T cell repertoire of CCA is characterized by increased TCR richness and decreased clonal expansion in women with preterm labor. We identified 15 clones associated with CCA and compared these against established TCR databases, reporting that infiltrating T cells may possess specificity for maternal and fetal Ags, but not common viral Ags. Functional assays demonstrated that choriodecidual T cells can respond to maternal and fetal Ags. Collectively, our findings provide, to our knowledge, novel insight into the complex processes underlying chronic placental inflammation and further support a role for effector T cells in the mechanisms of disease for preterm labor and birth. Moreover, this work further strengthens the contribution of adaptive immunity to the syndromic nature of preterm labor and birth.

A key role for NLRP3 signaling in preterm labor and birth driven by the alarmin S100B

Preterm birth remains the leading cause of neonatal morbidity and mortality worldwide. A substantial number of spontaneous preterm births occur in the context of sterile intra-amniotic inflammation, a condition that has been mechanistically proven to be triggered by alarmins. However, sterile intra-amniotic inflammation still lacks treatment. The NLRP3 inflammasome has been implicated in sterile intra-amniotic inflammation; yet, its underlying mechanisms, as well as the maternal and fetal contributions to this signaling pathway, are unclear. Herein, by utilizing a translational and clinically relevant model of alarmin-induced preterm labor and birth in Nlrp3-/- mice, we investigated the role of NLRP3 signaling by using imaging and molecular biology approaches. Nlrp3 deficiency abrogated preterm birth and the resulting neonatal mortality induced by the alarmin S100B by impeding the premature activation of the common pathway of labor as well as by dampening intra-amniotic and fetal inflammation. Moreover, Nlrp3 deficiency altered leukocyte infiltration and functionality in the uterus and decidua. Last, embryo transfer revealed that maternal and fetal Nlrp3 signaling contribute to alarmin-induced preterm birth and neonatal mortality, further strengthening the concept that both individuals participate in the complex process of preterm parturition. These findings provide novel insights into sterile intra-amniotic inflammation, a common etiology of preterm labor and birth, suggesting that the adverse perinatal outcomes resulting from prematurity can be prevented by targeting NLRP3 signaling.

Pregnancy-specific responses to COVID-19 revealed by high-throughput proteomics of human plasma

BACKGROUND

Pregnant women are at greater risk of adverse outcomes, including mortality, as well as obstetrical complications resulting from COVID-19. However, pregnancy-specific changes that underlie such worsened outcomes remain unclear.

METHODS

Plasma samples were collected from pregnant women and non-pregnant individuals (male and female) with (n = 72 pregnant, 52 non-pregnant) and without (n = 29 pregnant, 41 non-pregnant) COVID-19. COVID-19 patients were grouped as asymptomatic, mild, moderate, severe, or critically ill according to NIH classifications. Proteomic profiling of 7,288 analytes corresponding to 6,596 unique protein targets was performed using the SOMAmer platform.

RESULTS

Herein, we profile the plasma proteome of pregnant and non-pregnant COVID-19 patients and controls and show alterations that display a dose-response relationship with disease severity; yet, such proteomic perturbations are dampened during pregnancy. In both pregnant and non-pregnant state, the proteome response induced by COVID-19 shows enrichment of mediators implicated in cytokine storm, endothelial dysfunction, and angiogenesis. Shared and pregnancy-specific proteomic changes are identified: pregnant women display a tailored response that may protect the conceptus from heightened inflammation, while non-pregnant individuals display a stronger response to repel infection. Furthermore, the plasma proteome can accurately identify COVID-19 patients, even when asymptomatic or with mild symptoms.

CONCLUSION

This study represents the most comprehensive characterization of the plasma proteome of pregnant and non-pregnant COVID-19 patients. Our findings emphasize the distinct immune modulation between the non-pregnant and pregnant states, providing insight into the pathogenesis of COVID-19 as well as a potential explanation for the more severe outcomes observed in pregnant women.

Molecular subclasses of preeclampsia characterized by a longitudinal maternal proteomics study: distinct biomarkers, disease pathways and options for prevention

OBJECTIVES

The heterogeneous nature of preeclampsia is a major obstacle to early screening and prevention, and a molecular taxonomy of disease is needed. We have previously identified four subclasses of preeclampsia based on first-trimester plasma proteomic profiles. Herein, we expanded this approach by using a more comprehensive panel of proteins profiled in longitudinal samples.

METHODS

Proteomic data collected longitudinally from plasma samples of women who developed preeclampsia (n=109) and of controls (n=90) were available from our previous report on 1,125 proteins. Consensus clustering was performed to identify subgroups of patients with preeclampsia based on data from five gestational-age intervals by using select interval-specific features. Demographic, clinical, and proteomic differences among clusters were determined. Differentially abundant proteins were used to identify cluster-specific perturbed KEGG pathways.

RESULTS

Four molecular clusters with different clinical phenotypes were discovered by longitudinal proteomic profiling. Cluster 1 involves metabolic and prothrombotic changes with high rates of early-onset preeclampsia and small-for-gestational-age neonates; Cluster 2 includes maternal anti-fetal rejection mechanisms and recurrent preeclampsia cases; Cluster 3 is associated with extracellular matrix regulation and comprises cases of mostly mild, late-onset preeclampsia; and Cluster 4 is characterized by angiogenic imbalance and a high prevalence of early-onset disease.

CONCLUSIONS

This study is an independent validation and further refining of molecular subclasses of preeclampsia identified by a different proteomic platform and study population. The results lay the groundwork for novel diagnostic and personalized tools of prevention.

Human Plasma Proteome During Normal Pregnancy

The human plasma proteome is underexplored despite its potential value for monitoring health and disease. Herein, using a recently developed aptamer-based platform, we profiled 7288 proteins in 528 plasma samples from 91 normal pregnancies (Gene Expression Omnibus identifier GSE206454). The coefficient of variation was <20% for 93% of analytes (median 7%), and a cross-platform correlation for selected key angiogenic and anti-angiogenic proteins was significant. Gestational age was associated with changes in 953 proteins, including highly modulated placenta- and decidua-specific proteins, and they were enriched in biological processes including regulation of growth, angiogenesis, immunity, and inflammation. The abundance of proteins corresponding to RNAs specific to populations of cells previously described by single-cell RNA-Seq analysis of the placenta was highly modulated throughout gestation. Furthermore, machine learning-based prediction of gestational age and of time from sampling to term delivery compared favorably with transcriptomic models (mean absolute error of 2 weeks). These results suggested that the plasma proteome may provide a non-invasive readout of placental cellular dynamics and serve as a blueprint for investigating obstetrical disease.

Pregnancy-specific responses to COVID-19 are revealed by high-throughput proteomics of human plasma

Pregnant women are at greater risk of adverse outcomes, including mortality, as well as obstetrical complications resulting from COVID-19. However, pregnancy-specific changes that underlie such worsened outcomes remain unclear. Herein, we profiled the plasma proteome of pregnant and non-pregnant COVID-19 patients and controls and showed alterations that display a dose-response relationship with disease severity; yet, such proteomic perturbations are dampened during pregnancy. In both pregnant and non-pregnant state, the proteome response induced by COVID-19 showed enrichment of mediators implicated in cytokine storm, endothelial dysfunction, and angiogenesis. Shared and pregnancy-specific proteomic changes were identified: pregnant women display a tailored response that may protect the conceptus from heightened inflammation, while non-pregnant individuals display a stronger response to repel infection. Furthermore, the plasma proteome can accurately identify COVID-19 patients, even when asymptomatic or with mild symptoms. This study represents the most comprehensive characterization of the plasma proteome of pregnant and non-pregnant COVID-19 patients.

Maternal circulating concentrations of soluble Fas and Elabela in early- and late-onset preeclampsia

OBJECTIVE

The Fas/Fas ligand (FASL) system and Elabela-apelin receptor signaling pathways are implicated in the pathophysiology of preeclampsia. The aim of the current study was to investigate whether a model combining the measurement of sFas and Elabela in the maternal circulation may serve as a clinical biomarker for early- and/or late-onset preeclampsia more effectively than measures of each biomarker individually.

METHODS

Blood samples were collected from 214 women in the following groups: (1) normal pregnancy sampled <34 weeks of gestation (n = 56); (2) patients who developed early-onset preeclampsia (n = 54); (3) normal pregnancy sampled ≥34 weeks of gestation (n = 52); (4) patients who developed late-onset preeclampsia (n = 52). Maternal circulating soluble Fas and Elabela concentrations were determined using sensitive and validated immunoassays. Two sample t-tests, multivariate logistic regression, and receiver operating characteristic curves were used for analyses.

RESULTS

(1) Women with early-onset preeclampsia, and those with late-onset preeclampsia with placental lesions of maternal vascular malperfusion, had increased concentrations of sFas compared to their gestational age-matched normal controls; (2) women with late-onset preeclampsia, but not those with early-onset preeclampsia, had increased concentrations of Elabela compared to their gestational age-matched counterparts; and (3) an increase in both Elabela and sFas concentrations was more strongly associated with late-onset preeclampsia than early-onset preeclampsia relative to models including either of the markers alone.

CONCLUSIONS

A combined model of maternal sFas and Elabela concentrations provides a stronger association with late-onset preeclampsia than either protein alone. This finding demonstrates the possibility to improve the classification of late-onset preeclampsia by combining the results of both molecular biomarkers.

Gestational Age Dependence of the Maternal Circulating Long Non-Coding RNA Transcriptome During Normal Pregnancy Highlights Antisense and Pseudogene Transcripts

In the post-genomic era, our understanding of the molecular regulators of physiologic and pathologic processes in pregnancy is expanding at the whole-genome level. Longitudinal changes in the known protein-coding transcriptome during normal pregnancy, which we recently reported (Gomez-Lopez et al., 2019), have improved our definition of the major operant networks, yet pregnancy-related functions of the non-coding RNA transcriptome remain poorly understood. A key finding of the ENCODE (Encyclopedia of DNA Elements) Consortium, the successor of the Human Genome Project, was that the human genome contains approximately 60,000 genes, the majority of which do not encode proteins. The total transcriptional output of non-protein-coding RNA genes, collectively referred to as the non-coding transcriptome, is comprised mainly of long non-coding RNA (lncRNA) transcripts (Derrien et al., 2012). Although the ncRNA transcriptome eclipses its protein-coding counterpart in abundance, it has until recently lacked a comprehensive, unbiased, genome-scale characterization over the timecourse of normal human pregnancy. Here, we annotated, characterized, and selectively validated the longitudinal changes in the non-coding transcriptome of maternal whole blood during normal pregnancy to term. We identified nine long non-coding RNAs (lncRNAs), including long intergenic non-coding RNAs (lincRNAs) as well as lncRNAs antisense to or otherwise in the immediate vicinity of protein-coding genes, that were differentially expressed with advancing gestation in normal pregnancy: AL355711, BC039551 (expressed mainly in the placenta), JHDM1D-AS1, A2M-AS1, MANEA-AS1, NR_034004, LINC00649, LINC00861, and LINC01094. By cross-referencing our dataset against major public pseudogene catalogs, we also identified six transcribed pseudogenes that were differentially expressed over time during normal pregnancy in maternal blood: UBBP4, FOXO3B, two Makorin (MKRN) pseudogenes (MKRN9P and LOC441455), PSME2P2, and YBX3P1. We also identified three non-coding RNAs belonging to other classes that were modulated during gestation: the microRNA MIR4439, the small nucleolar RNA (snoRNA) SNORD41, and the small Cajal-body specific ncRNA SCARNA2. The expression profiles of most hits were broadly suggestive of functions in pregnancy. These time-dependent changes of the non-coding transcriptome during normal pregnancy, which may confer specific regulatory impacts on their protein-coding gene targets, will facilitate a deeper molecular understanding of pregnancy and lncRNA-mediated molecular pathways at the maternal-fetal interface and of how these pathways impact maternal and fetal health.

Transcriptome changes in maternal peripheral blood during term parturition mimic perturbations preceding spontaneous Preterm birth†

The complex physiologic process of parturition includes the onset of labor, which requires the orchestrated stimulation of a common pathway involving uterine contractility, cervical ripening, and chorioamniotic membrane activation. However, the labor-specific processes taking place in these tissues have limited use as predictive biomarkers unless they can be probed in non-invasive samples, such as the peripheral blood. Herein, we utilized a transcriptomic dataset to assess labor-specific changes in the peripheral blood of women who delivered at term. We identified a set of genes that were differentially expressed with labor and enriched for immunological processes, and these gene expression changes were strongly correlated with results from prior studies, providing in silico validation of our findings. We then identified significant correlations between labor-specific transcriptomic changes in the maternal circulation and those reported in the chorioamniotic membranes, myometrium, and cervix of women at term, demonstrating that tissue-specific labor signatures are partly mirrored in the peripheral blood. Last, we demonstrated a significant overlap between the peripheral blood transcriptomic changes in term parturition and those observed in asymptomatic women prior to the diagnosis of preterm prelabor rupture of membranes who delivered preterm. Collectively, we provide evidence that the normal process of labor at term is characterized by a unique immunological expression signature, which may serve as a useful tool for assessing labor status and potentially identifying women at risk for preterm birth.

The Distinct Immune Nature of the Fetal Inflammatory Response Syndrome Type I and Type II

Fetal inflammatory response syndrome (FIRS) is strongly associated with neonatal morbidity and mortality and can be classified as type I or type II. Clinically, FIRS type I and type II are considered as distinct syndromes, yet the molecular underpinnings of these fetal inflammatory responses are not well understood because of their low prevalence and the difficulty of postdelivery diagnosis. In this study, we performed RNA sequencing of human cord blood samples from preterm neonates diagnosed with FIRS type I or FIRS type II. We found that FIRS type I was characterized by an upregulation of host immune responses, including neutrophil and monocyte functions, together with a proinflammatory cytokine storm and a downregulation of T cell processes. In contrast, FIRS type II comprised a mild chronic inflammatory response involving perturbation of HLA transcripts, suggestive of fetal semiallograft rejection. Integrating single-cell RNA sequencing-derived signatures with bulk transcriptomic data confirmed that FIRS type I immune responses were mainly driven by monocytes, macrophages, and neutrophils. Last, tissue- and cell-specific signatures derived from the BioGPS Gene Atlas further corroborated the role of myeloid cells originating from the bone marrow in FIRS type I. Collectively, these data provide evidence that FIRS type I and FIRS type II are driven by distinct immune mechanisms; whereas the former involves the innate limb of immunity consistent with host defense, the latter resembles a process of semiallograft rejection. These findings shed light on the fetal immune responses caused by infection or alloreactivity that can lead to deleterious consequences in neonatal life.

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

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27-33 weeks of gestation).

Regulatory T Cells Play a Role in a Subset of Idiopathic Preterm Labor/Birth and Adverse Neonatal Outcomes

Regulatory T cells (Tregs) have been exhaustively investigated during early pregnancy; however, their role later in gestation is poorly understood. Herein, we report that functional Tregs are reduced at the maternal-fetal interface in a subset of women with idiopathic preterm labor/birth, which is accompanied by a concomitant increase in Tc17 cells. In mice, depletion of functional Tregs during late gestation induces preterm birth and adverse neonatal outcomes, which are rescued by the adoptive transfer of such cells. Treg depletion does not alter obstetrical parameters in the mother, yet it increases susceptibility to endotoxin-induced preterm birth. The mechanisms whereby depletion of Tregs induces adverse perinatal outcomes involve tissue-specific immune responses and mild systemic maternal inflammation, together with dysregulation of developmental and cellular processes in the placenta, in the absence of intra-amniotic inflammation. These findings provide mechanistic evidence supporting a role for Tregs in the pathophysiology of idiopathic preterm labor/birth and adverse neonatal outcomes.

Human Chorionic Gonadotropin Modulates the Transcriptome of the Myometrium and Cervix in Late Gestation

Human chorionic gonadotropin (hCG) is a critical hormone for the establishment and maintenance of pregnancy. hCG administration prevents the onset of preterm labor in mice; yet, the transcriptomic changes associated with this tocolytic effect that take place in the myometrium and cervix have not been elucidated. Herein, we implemented both discovery and targeted approaches to investigate the transcriptome of the myometrium and cervix after hCG administration. Pregnant mice were intraperitoneally injected with 10 IU of hCG on 13.0, 15.0, and 17.0 days post coitum, and the myometrium and cervix were collected. RNA sequencing was performed to determine differentially expressed genes, enriched biological processes, and impacted KEGG pathways. Multiplex qRT-PCR was performed to investigate the expression of targeted contractility- and inflammation-associated transcripts. hCG administration caused the differential expression of 720 genes in the myometrium. Among the downregulated genes, enriched biological processes were primarily associated with regulation of transcription. hCG administration downregulated key contractility genes, Gja1 and Oxtr, but upregulated the prostaglandin-related genes Ptgfr and Ptgs2 and altered the expression of inflammation-related genes in the myometrium. In the cervix, hCG administration caused differential expression of 3348 genes that were related to inflammation and host defense, among others. The downregulation of key contractility genes and upregulation of prostaglandin-related genes were also observed in the cervix. Thus, hCG exerts tocolytic and immunomodulatory effects in late gestation by altering biological processes in the myometrium and cervix, which should be taken into account when considering hCG as a potential treatment to prevent the premature onset of labor.

RNA Sequencing Reveals Diverse Functions of Amniotic Fluid Neutrophils and Monocytes/Macrophages in Intra-Amniotic Infection

Intra-amniotic infection, the invasion of microbes into the amniotic cavity resulting in inflammation, is a clinical condition that can lead to adverse pregnancy outcomes for the mother and fetus as well as severe long-term neonatal morbidities. Despite much research focused on the consequences of intra-amniotic infection, there remains little knowledge about the innate immune cells that respond to invading microbes. We performed RNA-seq of sorted amniotic fluid neutrophils and monocytes/macrophages from women with intra-amniotic infection to determine the transcriptomic differences between these innate immune cells. Further, we sought to identify specific transcriptomic pathways that were significantly altered by the maternal or fetal origin of amniotic fluid neutrophils and monocytes/macrophages, the presence of a severe fetal inflammatory response, and pregnancy outcome (i.e., preterm or term delivery). We show that significant transcriptomic differences exist between amniotic fluid neutrophils and monocytes/macrophages from women with intra-amniotic infection, indicating the distinct roles these cells play. The transcriptome of amniotic fluid immune cells varies based on their maternal or fetal origin, and the significant transcriptomic differences between fetal and maternal monocytes/macrophages imply that those of fetal origin exhibit impaired functions. Notably, transcriptomic changes in amniotic fluid monocytes/macrophages suggest that these immune cells collaborate with neutrophils in the trafficking of fetal leukocytes throughout the umbilical cord (i.e., funisitis). Finally, amniotic fluid neutrophils and monocytes/macrophages from preterm deliveries display enhanced transcriptional activity compared to those from term deliveries, highlighting the protective role of these cells during this vulnerable period. Collectively, these findings demonstrate the underlying complexity of local innate immune responses in women with intra-amniotic infection and provide new insights into the functions of neutrophils and monocytes/macrophages in the amniotic cavity.

Pregnancy-specific transcriptional changes upon endotoxin exposure in mice

Objectives Pregnant women are more susceptible to certain infections; however, this increased susceptibility is not fully understood. Herein, systems biology approaches were utilized to elucidate how pregnancy modulates tissue-specific host responses to a bacterial product, endotoxin. Methods Pregnant and non-pregnant mice were injected with endotoxin or saline on 16.5 days post coitum (n=8-11 per group). The uterus, cervix, liver, adrenal gland, kidney, lung, and brain were collected 12 h after injection and transcriptomes were measured using microarrays. Heatmaps and principal component analysis were used for visualization. Differentially expressed genes between groups were assessed using linear models that included interaction terms to determine whether the effect of infection differed with pregnancy status. Pathway analysis was conducted to interpret gene expression changes. Results We report herein a multi-organ atlas of the transcript perturbations in pregnant and non-pregnant mice in response to endotoxin. Pregnancy strongly modified the host responses to endotoxin in the uterus, cervix, and liver. In contrast, pregnancy had a milder effect on the host response to endotoxin in the adrenal gland, lung, and kidney. However, pregnancy did not drastically affect the host response to endotoxin in the brain. Conclusions Pregnancy imprints organ-specific host immune responses upon endotoxin exposure. These findings provide insight into the host-response against microbes during pregnancy.

Amniotic fluid cell-free transcriptome: a glimpse into fetal development and placental cellular dynamics during normal pregnancy

Background

The amniotic fluid (AF) cell-free transcriptome is modulated by physiologic and pathologic processes during pregnancy. AF gene expression changes with advancing gestation reflect fetal development and organ maturation; yet, defining normal expression and splicing patterns for biomarker discovery in obstetrics requires larger heterogeneous cohorts, evaluation of potential confounding factors, and novel analytical approaches.

Methods

Women with a normal pregnancy who had an AF sample collected during midtrimester (n = 30) or at term gestation (n = 68) were included. Expression profiling at exon level resolution was performed using Human Transcriptome Arrays. Differential expression was based on moderated t-test adjusted p < 0.05 and fold change > 1.25; for differential splicing, a splicing index > 2 and adjusted p < 0.05 were required. Functional profiling was used to interpret differentially expressed or spliced genes. The expression of tissue-specific and cell-type specific signatures defined by single-cell genomics was quantified and correlated with covariates. In-silico validation studies were performed using publicly available datasets.

Results

1) 64,071 genes were detected in AF, with 11% of the coding and 6% of the non-coding genes being differentially expressed between midtrimester and term gestation. Expression changes were highly correlated with those previously reported (R > 0.79, p < 0.001) and featured increased expression of genes specific to the trachea, salivary glands, and lung and decreased expression of genes specific to the cardiac myocytes, uterus, and fetal liver, among others. 2) Single-cell RNA-seq signatures of the cytotrophoblast, Hofbauer cells, erythrocytes, monocytes, T and B cells, among others, showed complex patterns of modulation with gestation (adjusted p < 0.05). 3) In 17% of the genes detected, we found differential splicing with advancing gestation in genes related to brain development processes and immunity pathways, including some that were missed based on differential expression analysis alone.

Conclusions

This represents the largest AF transcriptomics study in normal pregnancy, reporting for the first time that single-cell genomic signatures can be tracked in the AF and display complex patterns of expression during gestation. We also demonstrate a role for alternative splicing in tissue-identity acquisition, organ development, and immune processes. The results herein may have implications for the development of fetal testing to assess placental function and fetal organ maturity.

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

OBJECTIVES

To identify maternal plasma protein markers for early preeclampsia (delivery <34 weeks of gestation) and to determine whether the prediction performance is affected by disease severity and presence of placental lesions consistent with maternal vascular malperfusion (MVM) among cases.

STUDY DESIGN

This longitudinal case-control study included 90 patients with a normal pregnancy and 33 patients with early preeclampsia. Two to six maternal plasma samples were collected throughout gestation from each woman. The abundance of 1,125 proteins was measured using high-affinity aptamer-based proteomic assays, and data were modeled using linear mixed-effects models. After data transformation into multiples of the mean values for gestational age, parsimonious linear discriminant analysis risk models were fit for each gestational-age interval (8-16, 16.1-22, 22.1-28, 28.1-32 weeks). Proteomic profiles of early preeclampsia cases were also compared to those of a combined set of controls and late preeclampsia cases (n = 76) reported previously. Prediction performance was estimated via bootstrap.

RESULTS

We found that 1) multi-protein models at 16.1-22 weeks of gestation predicted early preeclampsia with a sensitivity of 71% at a false-positive rate (FPR) of 10%. High abundance of matrix metalloproteinase-7 and glycoprotein IIbIIIa complex were the most reliable predictors at this gestational age; 2) at 22.1-28 weeks of gestation, lower abundance of placental growth factor (PlGF) and vascular endothelial growth factor A, isoform 121 (VEGF-121), as well as elevated sialic acid binding immunoglobulin-like lectin 6 (siglec-6) and activin-A, were the best predictors of the subsequent development of early preeclampsia (81% sensitivity, FPR = 10%); 3) at 28.1-32 weeks of gestation, the sensitivity of multi-protein models was 85% (FPR = 10%) with the best predictors being activated leukocyte cell adhesion molecule, siglec-6, and VEGF-121; 4) the increase in siglec-6, activin-A, and VEGF-121 at 22.1-28 weeks of gestation differentiated women who subsequently developed early preeclampsia from those who had a normal pregnancy or developed late preeclampsia (sensitivity 77%, FPR = 10%); 5) the sensitivity of risk models was higher for early preeclampsia with placental MVM lesions than for the entire early preeclampsia group (90% versus 71% at 16.1-22 weeks; 87% versus 81% at 22.1-28 weeks; and 90% versus 85% at 28.1-32 weeks, all FPR = 10%); and 6) the sensitivity of prediction models was higher for severe early preeclampsia than for the entire early preeclampsia group (84% versus 71% at 16.1-22 weeks).

CONCLUSION

We have presented herein a catalogue of proteome changes in maternal plasma proteome that precede the diagnosis of preeclampsia and can distinguish among early and late phenotypes. The sensitivity of maternal plasma protein models for early preeclampsia is higher in women with underlying vascular placental disease and in those with a severe phenotype.

Effector and Activated T Cells Induce Preterm Labor and Birth That Is Prevented by Treatment with Progesterone

Preterm labor commonly precedes preterm birth, the leading cause of perinatal morbidity and mortality worldwide. Most research has focused on establishing a causal link between innate immune activation and pathological inflammation leading to preterm labor and birth. However, the role of maternal effector/activated T cells in the pathogenesis of preterm labor/birth is poorly understood. In this study, we first demonstrated that effector memory and activated maternal T cells expressing granzyme B and perforin are enriched at the maternal-fetal interface (decidua) of women with spontaneous preterm labor. Next, using a murine model, we reported that prior to inducing preterm birth, in vivo T cell activation caused maternal hypothermia, bradycardia, systemic inflammation, cervical dilation, intra-amniotic inflammation, and fetal growth restriction, all of which are clinical signs associated with preterm labor. In vivo T cell activation also induced B cell cytokine responses, a proinflammatory macrophage polarization, and other inflammatory responses at the maternal-fetal interface and myometrium in the absence of an increased influx of neutrophils. Finally, we showed that treatment with progesterone can serve as a strategy to prevent preterm labor/birth and adverse neonatal outcomes by attenuating the proinflammatory responses at the maternal-fetal interface and cervix induced by T cell activation. Collectively, these findings provide mechanistic evidence showing that effector and activated T cells cause pathological inflammation at the maternal-fetal interface, in the mother, and in the fetus, inducing preterm labor and birth and adverse neonatal outcomes. Such adverse effects can be prevented by treatment with progesterone, a clinically approved strategy.

A soft cervix, categorized by shear-wave elastography, in women with short or with normal cervical length at 18-24 weeks is associated with a higher prevalence of spontaneous preterm delivery

OBJECTIVE

To determine whether a soft cervix identified by shear-wave elastography between 18 and 24 weeks of gestation is associated with increased frequency of spontaneous preterm delivery (sPTD).

MATERIALS AND METHODS

This prospective cohort study included 628 consecutive women with a singleton pregnancy. Cervical length (mm) and softness [shear-wave speed: (SWS) meters per second (m/s)] of the internal cervical os were measured at 18-24 weeks of gestation. Frequency of sPTD <37 (sPTD<37) and <34 (sPTD<34) weeks of gestation was compared among women with and without a short (≤25 mm) and/or a soft cervix (SWS <25th percentile).

RESULTS

There were 31/628 (4.9%) sPTD<37 and 12/628 (1.9%) sPTD<34 deliveries. The combination of a soft and a short cervix increased the risk of sPTD<37 by 18-fold [relative risk (RR) 18.0 (95% confidence interval [CI], 7.7-43.9); P<0.0001] and the risk of sPTD<34 by 120-fold [RR 120.0 (95% CI 12.3-1009.9); P<0.0001] compared to women with normal cervical length. A soft-only cervix increased the risk of sPTD<37 by 4.5-fold [RR 4.5 (95% CI 2.1-9.8); P=0.0002] and of sPTD<34 by 21-fold [RR 21.0 (95% CI 2.6-169.3); P=0.0003] compared to a non-soft cervix.

CONCLUSIONS

A soft cervix at 18-24 weeks of gestation increases the risk of sPTD <37 and <34 weeks of gestation independently of cervical length.

Inflammation-Induced Adverse Pregnancy and Neonatal Outcomes Can Be Improved by the Immunomodulatory Peptide Exendin-4

Preterm birth is the leading cause of neonatal morbidity and mortality worldwide. Inflammation is causally linked to preterm birth; therefore, finding an intervention that dampens maternal and fetal inflammatory responses may provide a new strategy to prevent adverse pregnancy and neonatal outcomes. Using animal models of systemic maternal inflammation [intraperitoneal injection of lipopolysaccharide (LPS)] and fetal inflammation (intra-amniotic administration of LPS), we found that (1) systemic inflammation induced adverse pregnancy and neonatal outcomes by causing a severe maternal cytokine storm and a mild fetal cytokine response; (2) fetal inflammation induced adverse pregnancy and neonatal outcomes by causing a mild maternal cytokine response and a severe fetal cytokine storm; (3) exendin-4 (Ex4) treatment of dams with systemic inflammation or fetal inflammation improved adverse pregnancy outcomes by modestly reducing the rate of preterm birth; (4) Ex4 treatment of dams with systemic, but not local, inflammation considerably improved neonatal outcomes, and such neonates continued to thrive; (5) systemic inflammation facilitated the diffusion of Ex4 through the uterus and the maternal-fetal interface; (6) neonates born to Ex4-treated dams with systemic inflammation displayed a similar cytokine profile to healthy control neonates; and (7) treatment with Ex4 had immunomodulatory effects by inducing an M2 macrophage polarization and increasing anti-inflammatory neutrophils, as well as suppressing the expansion of CD8+ regulatory T cells, in neonates born to dams with systemic inflammation. Collectively, these results provide evidence that dampening maternal systemic inflammation through novel interventions, such as Ex4, can improve the quality of life for neonates born to women with this clinical condition.

A Low Cerebroplacental Ratio at 20-24 Weeks of Gestation Can Predict Reduced Fetal Size Later in Pregnancy or at Birth

AIM

To determine whether Doppler evaluation at 20-24 weeks of gestation can predict reduced fetal size later in pregnancy or at birth.

METHODS

Fetal biometry and Doppler velocimetry were performed in 2,986 women with a singleton pregnancy at 20-24 weeks of gestation. Predictive performances of the umbilical artery pulsatility index (UA-PI) or the mean uterine artery pulsatility index (UtA-PI) >95th percentile, middle cerebral artery pulsatility index, or cerebroplacental ratio (CPR) <5th percentile for early small for gestational age (SGA; <34 weeks of gestation), late SGA (≥34 weeks of gestation), or SGA at birth (birthweight <10th percentile) were analyzed.

RESULTS

The prevalence of early SGA, late SGA, and SGA at birth was 1.1, 9.6, and 14.7%, respectively. A CPR <5th percentile had a positive likelihood ratio (LR+) of 8.2 (95% confidence interval [CI] 5.7-12.0) for early SGA, a LR+ of 1.6 (95% CI 1.1-1.2) for late SGA, and a LR+ of 1.9 (95% CI 1.4-2.6) for SGA at birth. A UtA-PI >95th percentile was associated with late SGA and SGA at birth, while an UA-PI >95th percentile was associated with early SGA. Associations were higher in fetuses with an estimated fetal weight <10th percentile.

CONCLUSION

Fetal biometry and Doppler evaluation at 20-24 weeks of gestation can predict early and late SGA as well as SGA at birth.

The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study

BACKGROUND

Late-onset preeclampsia is the most prevalent phenotype of this syndrome; nevertheless, only a few biomarkers for its early diagnosis have been reported. We sought to correct this deficiency using a high through-put proteomic platform.

METHODS

A case-control longitudinal study was conducted, including 90 patients with normal pregnancies and 76 patients with late-onset preeclampsia (diagnosed at ≥34 weeks of gestation). Maternal plasma samples were collected throughout gestation (normal pregnancy: 2-6 samples per patient, median of 2; late-onset preeclampsia: 2-6, median of 5). The abundance of 1,125 proteins was measured using an aptamers-based proteomics technique. Protein abundance in normal pregnancies was modeled using linear mixed-effects models to estimate mean abundance as a function of gestational age. Data was then expressed as multiples of-the-mean (MoM) values in normal pregnancies. Multi-marker prediction models were built using data from one of five gestational age intervals (8-16, 16.1-22, 22.1-28, 28.1-32, 32.1-36 weeks of gestation). The predictive performance of the best combination of proteins was compared to placental growth factor (PIGF) using bootstrap.

RESULTS

1) At 8-16 weeks of gestation, the best prediction model included only one protein, matrix metalloproteinase 7 (MMP-7), that had a sensitivity of 69% at a false positive rate (FPR) of 20% (AUC = 0.76); 2) at 16.1-22 weeks of gestation, MMP-7 was the single best predictor of late-onset preeclampsia with a sensitivity of 70% at a FPR of 20% (AUC = 0.82); 3) after 22 weeks of gestation, PlGF was the best predictor of late-onset preeclampsia, identifying 1/3 to 1/2 of the patients destined to develop this syndrome (FPR = 20%); 4) 36 proteins were associated with late-onset preeclampsia in at least one interval of gestation (after adjustment for covariates); 5) several biological processes, such as positive regulation of vascular endothelial growth factor receptor signaling pathway, were perturbed; and 6) from 22.1 weeks of gestation onward, the set of proteins most predictive of severe preeclampsia was different from the set most predictive of the mild form of this syndrome.

CONCLUSIONS

Elevated MMP-7 early in gestation (8-22 weeks) and low PlGF later in gestation (after 22 weeks) are the strongest predictors for the subsequent development of late-onset preeclampsia, suggesting that the optimal identification of patients at risk may involve a two-step diagnostic process.

The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study

OBJECTIVE

Pregnancy is accompanied by dramatic physiological changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age and determine biological processes that are perturbed in normal pregnancy.

STUDY DESIGN

A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median, 5) were profiled to measure the abundance of 1125 proteins using multiplex assays. Linear mixed-effects models with polynomial splines were used to model protein abundance as a function of gestational age, and the significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having the following: (1) >1.5-fold change between 8 and 40 weeks of gestation; and (2) a false discovery rate-adjusted value of P < .1. Gene ontology enrichment analysis was used to identify biological processes overrepresented among the proteins that changed with advancing gestation.

RESULTS

The following results were found: (1) Ten percent (112 of 1125) of the profiled proteins changed in abundance as a function of gestational age; (2) of the 1125 proteins analyzed, glypican-3, sialic acid-binding immunoglobulin-type lectin-6, placental growth factor, C-C motif-28, carbonic anhydrase 6, prolactin, interleukin-1 receptor 4, dual-specificity mitogen-activated protein kinase 4, and pregnancy-associated plasma protein-A had more than a 5-fold change in abundance across gestation (these 9 proteins are known to be involved in a wide range of both physiological and pathological processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc); and (3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis, and leukocyte migration (false discovery rate, 10%).

CONCLUSION

The plasma proteome of normal pregnancy demonstrates dramatic changes in both the magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy and the development of biomarkers to differentiate normal vs abnormal pregnancy and determine the response to interventions.

Predicting novel human gene ontology annotations using semantic analysis

The correct interpretation of many molecular biology experiments depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are meant to act as repositories for our biological knowledge as we acquire and refine it. Hence, by definition, they are incomplete at any given time. In this paper, we describe a technique that improves our previous method for predicting novel GO annotations by extracting implicit semantic relationships between genes and functions. In this work, we use a vector space model and a number of weighting schemes in addition to our previous latent semantic indexing approach. The technique described here is able to take into consideration the hierarchical structure of the Gene Ontology (GO) and can weight differently GO terms situated at different depths. The prediction abilities of 15 different weighting schemes are compared and evaluated. Nine such schemes were previously used in other problem domains, while six of them are introduced in this paper. The best weighting scheme was a novel scheme, n2tn. Out of the top 50 functional annotations predicted using this weighting scheme, we found support in the literature for 84 percent of them, while 6 percent of the predictions were contradicted by the existing literature. For the remaining 10 percent, we did not find any relevant publications to confirm or contradict the predictions. The n2tn weighting scheme also outperformed the simple binary scheme used in our previous approach.

A semantic analysis of the annotations of the human genome

The correct interpretation of any biological experiment depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are ubiquitous and used by all life scientists in most experiments. However, it is well known that such databases are incomplete and many annotations may also be incorrect. In this paper we describe a technique that can be used to analyze the semantic content of such annotation databases. Our approach is able to extract implicit semantic relationships between genes and functions. This ability allows us to discover novel functions for known genes. This approach is able to identify missing and inaccurate annotations in existing annotation databases, and thus help improve their accuracy. We used our technique to analyze the current annotations of the human genome. From this body of annotations, we were able to predict 212 additional gene-function assignments. A subsequent literature search found that 138 of these gene-functions assignments are supported by existing peer-reviewed papers. An additional 23 assignments have been confirmed in the meantime by the addition of the respective annotations in later releases of the Gene Ontology database. Overall, the 161 confirmed assignments represent 75.95% of the proposed gene-function assignments. Only one of our predictions (0.4%) was contradicted by the existing literature. We could not find any relevant articles for 50 of our predictions (23.58%). The method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database.

Disablement and eye contact

This study investigated the effect of height level and wheelchair presence on eye contact and interaction. Presence of a wheelchair increased eye contact to a standing colleague, possibly due to the wheelchair-confined individuals' perceived dependence on others.