Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

Identification of PKD1L1 Gene Variants in Children with the Biliary Atresia Splenic Malformation Syndrome

Biliary atresia (BA) is the most common cause of end‐stage liver disease in children and the primary indication for pediatric liver transplantation, yet underlying etiologies remain unknown. Approximately 10% of infants affected by BA exhibit various laterality defects (heterotaxy) including splenic abnormalities and complex cardiac malformations — a distinctive subgroup commonly referred to as the biliary atresia splenic malformation (BASM) syndrome. We hypothesized that genetic factors linking laterality features with the etiopathogenesis of BA in BASM patients could be identified through whole exome sequencing (WES) of an affected cohort. DNA specimens from 67 BASM subjects, including 58 patient‐parent trios, from the NIDDK‐supported Childhood Liver Disease Research Network (ChiLDReN) underwent WES. Candidate gene variants derived from a pre‐specified set of 2,016 genes associated with ciliary dysgenesis and/or dysfunction or cholestasis were prioritized according to pathogenicity, population frequency, and mode of inheritance. Five BASM subjects harbored rare and potentially deleterious bi‐allelic variants in polycystin 1‐like 1, PKD1L1, a gene associated with ciliary calcium signaling and embryonic laterality determination in fish, mice and humans. Heterozygous PKD1L1 variants were found in 3 additional subjects. Immunohistochemical analysis of liver from the one BASM subject available revealed decreased PKD1L1 expression in bile duct epithelium when compared to normal livers and livers affected by other non‐cholestatic diseases. Conclusion WES identified bi‐allelic and heterozygous PKD1L1 variants of interest in 8 BASM subjects from the ChiLDReN dataset. The dual roles for PKD1L1 in laterality determination and ciliary function suggest that PKD1L1 is a new, biologically plausible, cholangiocyte‐expressed candidate gene for the BASM syndrome

Patterns of leisure-time physical activity across pregnancy and adverse pregnancy outcomes

Background Although leisure-time physical activity (PA) contributes to overall health, including pregnancy health, patterns across pregnancy have not been related to birth outcomes. We hypothesized that women with sustained low leisure-time PA would have excess risk of adverse pregnancy outcomes, and that changing patterns across pregnancy (high to low and low to high) may also be related to risk of adverse pregnancy outcomes. Methods Nulliparous women (n = 10,038) were enrolled at 8 centers early in pregnancy (mean gestational age in weeks [SD] = 12.05 [1.51]. Frequency, duration, and intensity (metabolic equivalents) of up to three leisure activities reported in the first, second and third trimesters were analyzed. Growth mixture modeling was used to identify leisure-time PA patterns across pregnancy. Adverse pregnancy outcomes (preterm birth, [PTB, overall and spontaneous], hypertensive disorders of pregnancy [HDP], gestational diabetes [GDM] and small-for-gestational-age births [SGA]) were assessed via chart abstraction. Results Five patterns of leisure-time PA across pregnancy were identified: High (35%), low (18%), late decreasing (24%), early decreasing (10%), and early increasing (13%). Women with sustained low leisure-time PA were younger and more likely to be black or Hispanic, obese, or to have smoked prior to pregnancy. Women with low vs. high leisure-time PA patterns had higher rates of PTB (10.4 vs. 7.5), HDP (13.9 vs. 11.4), and GDM (5.7 vs. 3.1, all p < 0.05). After adjusting for maternal factors (age, race/ethnicity, BMI and smoking), the risk of GDM (Odds ratio 2.00 [95% CI 1.47, 2.73]) remained higher in women with low compared to high patterns. Early and late decreasing leisure-time PA patterns were also associated with higher rates of GDM. In contrast, women with early increasing patterns had rates of GDM similar to the group with high leisure-time PA (3.8% vs. 3.1%, adjusted OR 1.16 [0.81, 1.68]). Adjusted risk of overall PTB (1.31 [1.05, 1.63]) was higher in the low pattern group, but spontaneous PTB, HDP and SGA were not associated with leisure-time PA patterns. Conclusions Sustained low leisure-time PA across pregnancy is associated with excess risk of GDM and overall PTB compared to high patterns in nulliparous women. Women with increased leisure-time PA early in pregnancy had low rates of GDM that were similar to women with high patterns, raising the possibility that early pregnancy increases in activity may be associated with improved pregnancy health. Trial registration Registration number NCT02231398

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

Motivation Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia. Results We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified. Availability and implementation Datasets and scripts for reproduction of results are available through: Https://nalab.stanford.edu/multiomics-pregnancy/

An immune clock of human pregnancy

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

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

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10−40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10−7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services

The Efficacy of Vaginal Clindamycin for the Treatment of Abnormal Genital Tract Flora in Pregnancy

Objective: To assess the efficacy of 2% clindamycin vaginal cream (CVC) to treat bacterial vaginosis (BV) in pregnancy. Methods: A prospective, randomized, double-blind, placebo-controlled, tricenter study. Four hundred and four women with BV on Gram stain at their first antenatal clinic visit were randomized to receive a 3-day course of 2% CVC or placebo. The outcome was assessed using an intention to treat analysis at 3 weeks and 6 weeks post-treatment according to three different diagnostic methods based on five criteria (Gram stain and all four elements of clinical composite criteria: vaginal discharge, abnormal vaginal pH, clue cells, amine odor), three criteria (vaginal pH, clue cells, amine odor) or two criteria (clue cells and amine odor) to reflect stringency of diagnosis, historical precedence and government agency recommendations respectively. Results: Using five diagnostic criteria, 18% of CVC patients were cured and 70.8% either cured and/or improved compared to 1.6% and 12% of placebo patients respectively (p < 0.0001). Using three diagnostic criteria, 44.8% of CVC patients were cured and 77.3% were either cured and/or improved compared to 9.3% and 28.8% of placebo patients respectively (p < 0.0001). Using two diagnostic criteria, 75.0% of CVC patients were cured compared to 18.0% of placebo patients (p < 0.0001). Recurrence rates in those CVC patients successfully treated were approximately 6% at 6 weeks post baseline and 10% at 28 to 34 weeks gestation. Conclusions: A 3-day course of CVC appears to be well tolerated by the mother and statistically significantly more efficacious than placebo in the treatment of BV during the second trimester of pregnancy

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts