Whole blood transcriptomics data in normal pregnancy, preterm birth and early preeclampsia
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ABSTRACT:
PROVIDER: PRJNA628905 | ENA |
REPOSITORIES: ENA
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Project description:Plasma proteomics in preterm birth and normal pregnancy
| PRJNA631286 | ENA
Project description:Whole blood transcriptomics data in preterm birth and early preeclampsia
| PRJNA628916 | ENA
Project description:Maternal plasma samples collected longitudinally from pregnant women were profiled using SomaLogic aptamer-based assays in women with normal pregnancy and those who delivered preterm. DiagnosisGA is the gestational age at diagnosis with any disease indicated by the Group variable, and it is set to NA for normal pregnancies. In the Group variable, sPTD stands for spontaneous preterm delivery, and PPROM for preterm premature rupture of membranes. Additional longitudinal samples of the controls, including the two samples included herein, are also available and described in PMID: 28738067.
2021-05-24 | GSE150167 | GEO
Project description:Peripheral whole blood transcriptome profiles of pregnant women with normal pregnancy and spontaneous preterm birth from 10-18 weeks of gestational age enrolled in the Vitamin D Antenatal Asthma Reduction Trial (VDAART).
2020-02-10 | GSE142974 | GEO
Project description:Preterm birth, defined as birth <37 weeks of gestation, is a leading cause of infant morbidity and mortality. In the United States, approximately 12% of all births are preterm.1 Despite decades of research, there has been little progress in developing effective interventions to prevent preterm birth. In fact, the rate of preterm birth has increased slightly over the last several decades.2 The ultimate goal of the Genomic and Proteomic Network for Preterm Birth Research (GPN-PBR) is to identify possible biomarkers that could predict the susceptibility to spontaneous preterm birth (SPTB) as well as to shed light on the molecular mechanisms involved in its etiologies. Understanding those mechanisms will help us predict SPTB and may facilitate the introduction of more effective prevention and treatment strategies.
2014-08-28 | PXD001268 | Pride
Project description:Preterm birth is a main determinant of neonatal mortality and morbidity and a major contributor to the overall mortality and burden of disease. However, precise phenotyping of the preterm birth is hampered by the imprecise definition of the clinical phenotype and complexity of the molecular phenotype due to multiple pregnancy tissue types and molecular processes that may contribute to the preterm birth. The studyâ??s aim was to comprehensively evaluate the mRNA transcriptome that characterizes preterm and term labor using precisely phenotyped samples. Expression profiles of 73 genes and non-coding RNA sequences uniquely identified the four groups of patients: delivering preterm with (PL) and without labor (PNL), term with (TL) and without labor (TNL). The largest differences in gene expression among the four groups occurred in decidua, chorion and amnion. The gene expression profiles showed suppression of chemokines expression in TNL, withdrawal of this suppression in TL, activation of multiple pathways of inflammation in PL, and an immune rejection profile in PNL. The genes constituting expression signatures showed over-representation of three putative regulatory elements in their 5â?? and 3â??UTR regions. The results suggest that pregnancy is maintained by downregulation of chemokines at the maternal-fetal interface. Withdrawal of this downregulation results in the term birth and its overriding by the activation of multiple pathways of the immune system in the preterm birth. Complications of the pregnancy associated with impairment of placental function, which necessitated premature delivery of the fetus in the absence of labor, show gene expression patterns associated with immune rejection. 183 total RNA samples from 8 tissue types collected from 35 women grouped into six categories of pregnancy outcome. One microarray replicate per sample. Other Contributors: Radek Bukowski, Sam Parry and the NICHD Genomic and Proteomic Network for Preterm Birth Research
2016-06-30 | E-GEOD-73685 | biostudies-arrayexpress
Project description:<p>The pregnancy vaginal microbiome contributes to risk of preterm birth, the primary cause of death in children under 5 years of age. Here we describe direct on-swab metabolic profiling by Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) for sample preparation-free characterisation of the cervicovaginal metabolome in two independent pregnancy cohorts (VMET, n = 160; 455 swabs; VMET II, n = 205; 573 swabs). By integrating metataxonomics and immune profiling data from matched samples, we show that specific metabolome signatures can be used to robustly predict simultaneously both the composition of the vaginal microbiome and host inflammatory status. In these patients, vaginal microbiota instability and innate immune activation, as predicted using DESI-MS, associated with preterm birth, including in women receiving cervical cerclage for preterm birth prevention. These findings highlight direct on-swab metabolic profiling by DESI-MS as an innovative approach for preterm birth risk stratification through rapid assessment of vaginal microbiota-host dynamics.</p><p><br></p><p><strong>Linked cross omic data sets:</strong></p><p>Meta-taxonomics data associated with this study are available in the European Nucleotide Archive (ENA): accession number <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB11895' rel='noopener noreferrer' target='_blank'>PRJEB11895</a>, <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB12577' rel='noopener noreferrer' target='_blank'>PRJEB12577</a> and <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB41427' rel='noopener noreferrer' target='_blank'>PRJEB41427</a>.</p>
2021-09-23 | MTBLS717 | MetaboLights
Project description:Maternal whole blood colected longitudinally were profiled using Affymetrix Human Transcriptome Arrays to evaluate prediction of gestational age in normal and complicated pregnancies and predict preterm birth. LMP is the date at the last menstrual period. Oper_LMP is the date at the last menstrual period with eventual adjustment based on ultrasound determination. Gestational age (GA) (weeks) is defined as (Date at sample - Oper_LMP)/7. For control pregnancies, SubGroup defines those with spontaneous labor at term (TL) as opposed with those delivered by cesarean section (TNL). Train is 1 if the sample was used in sub-challenge 1 in the training set as opposed to test set (0). D2 is 1 if the sample was used in the 2 interval prediction scenario, and if yes, it was assigned to the interval given by column D2Interval. D3 is 1 if the sample was used in the 3 interval prediction scenario, and if yes, it was assigned to the interval given by column D3Interval. DiagnosisGA is the gestational age at diagnosis with any disease indicated by the Group variable, and it is set to NA for normal pregnancies.
2021-05-24 | GSE149437 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-05-24 | GSE149440 | GEO
Project description:To identify the differential expression genes between Normal placenta and preterm birth placenta.
2024-08-06 | GSE239945 | GEO