Clinical Professor, Obstetrics & Gynecology - Maternal Fetal Medicine
View details for Web of Science ID 000423616600271
View details for Web of Science ID 000416950700088
The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling-based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2-dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies.
View details for DOI 10.1126/sciimmunol.aan2946
View details for PubMedID 28864494
Early detection of maladaptive processes underlying pregnancy-related pathologies is desirable, as it will enable targeted interventions ahead of clinical manifestations. The quantitative analysis of plasma proteins features prominently among molecular approaches used to detect deviations from normal pregnancy. However, derivation of proteomic signatures sufficiently predictive of pregnancy-related outcomes has been challenging. An important obstacle hindering such efforts were limitations in assay technology, which prevented the broad examination of the plasma proteome.The recent availability of a highly-multiplexed platform affording the simultaneous measurement of 1,310 plasma proteins opens the door for a more explorative approach. The major aim of this study was to examine whether analysis of plasma collected during gestation of term pregnancy would allow identifying a set of proteins that tightly track gestational age. Establishing precisely-timed plasma proteomic changes during term pregnancy is a critical step in identifying deviations from regular patterns due to fetal and maternal maladaptations. A second aim was to gain insight into functional attributes of identified proteins, and link such attributes to relevant immunological changes.Pregnant women participated in this longitudinal study. In two subsequent subsets of 21 (training cohort) and 10 (validation cohort) women, specific blood specimens were collected during the first (7-14 wks), second (15-20 wks), and third (24-32 wks) trimesters, and 6 wks post-partum for analysis with a highly-multiplexed aptamer-based platform. An elastic net algorithm was applied to infer a proteomic model predicting gestational age. A bootstrapping procedure and piece-wise regression analysis was used to extract the minimum number of proteins required for predicting gestational age without compromising predictive power. Gene ontology analysis was applied to infer enrichment of molecular functions among proteins included in the proteomic model. Changes in abundance of proteins with such functions were linked to immune features predictive of gestational age at the time of sampling in pregnancies delivering at term.An independently validated model consisting of 74 proteins strongly predicted gestational age (p = 3.8x10-14, R = 0.97). The model could be reduced to eight proteins without losing its predictive power (p = 1.7x10-3, R = 0.91). The three top ranked proteins were glypican 3, chorionic somatomammotropin hormone, and granulins. Proteins activating the Janus kinase (JAK) and signal transducer and activator of transcription (STAT) pathway were enriched in the proteomic model, chorionic somatomammotropin hormone being the top ranked protein. Abundance of chorionic somatomammotropin hormone strongly correlated with STAT5 signaling activity in CD4 T cells, the endogenous cell-signaling event most predictive of gestational age.Results indicate that precisely timed changes in the plasma proteome during term pregnancy mirror a "proteomic clock". Importantly, the combined use of several plasma proteins was required for accurate prediction. The exciting promise of such a "clock" is that deviations from its regular chronological profile may assist in the early diagnoses of pregnancy-relate pathologies and point to underlying pathophysiology. Functional analysis of the proteomic model generated the novel hypothesis that somatomammotropin hormone may critically regulate T-cell function during pregnancy.
View details for DOI 10.1016/j.ajog.2017.12.208
View details for PubMedID 29277631
View details for Web of Science ID 000414256401118
It is unclear whether using fetal electrocardiographic (ECG) ST-segment analysis as an adjunct to conventional intrapartum electronic fetal heart-rate monitoring modifies intrapartum and neonatal outcomes.We performed a multicenter trial in which women with a singleton fetus who were attempting vaginal delivery at more than 36 weeks of gestation and who had cervical dilation of 2 to 7 cm were randomly assigned to "open" or "masked" monitoring with fetal ST-segment analysis. The masked system functioned as a normal fetal heart-rate monitor. The open system displayed additional information for use when uncertain fetal heart-rate patterns were detected. The primary outcome was a composite of intrapartum fetal death, neonatal death, an Apgar score of 3 or less at 5 minutes, neonatal seizure, an umbilical-artery blood pH of 7.05 or less with a base deficit of 12 mmol per liter or more, intubation for ventilation at delivery, or neonatal encephalopathy.A total of 11,108 patients underwent randomization; 5532 were assigned to the open group, and 5576 to the masked group. The primary outcome occurred in 52 fetuses or neonates of women in the open group (0.9%) and 40 fetuses or neonates of women in the masked group (0.7%) (relative risk, 1.31; 95% confidence interval, 0.87 to 1.98; P=0.20). Among the individual components of the primary outcome, only the frequency of a 5-minute Apgar score of 3 or less differed significantly between neonates of women in the open group and those in the masked group (0.3% vs. 0.1%, P=0.02). There were no significant between-group differences in the rate of cesarean delivery (16.9% and 16.2%, respectively; P=0.30) or any operative delivery (22.8% and 22.0%, respectively; P=0.31). Adverse events were rare and occurred with similar frequency in the two groups.Fetal ECG ST-segment analysis used as an adjunct to conventional intrapartum electronic fetal heart-rate monitoring did not improve perinatal outcomes or decrease operative-delivery rates. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and Neoventa Medical; ClinicalTrials.gov number, NCT01131260.).
View details for DOI 10.1056/NEJMoa1500600
View details for Web of Science ID 000359707700008
View details for PubMedID 26267623