Ontology highlight
ABSTRACT:
PROVIDER: PRJNA544732 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9122770_1.fastq.gz | Fastqsanger.gz | |||
| SRR9122770_2.fastq.gz | Fastqsanger.gz | |||
| SRR9122780_1.fastq.gz | Fastqsanger.gz | |||
| SRR9122780_2.fastq.gz | Fastqsanger.gz | |||
| SRR9122790_1.fastq.gz | Fastqsanger.gz |
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Project description:Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted metabolomics on 232 second-trimester vaginal samples, 80 from pregnancies ending preterm. We find multiple associations between vaginal metabolites and subsequent preterm birth, and propose that several of these metabolites, including diethanolamine and ethyl glucoside, are exogenous. We observe associations between the metabolome and microbiome profiles previously obtained using 16S ribosomal RNA amplicon sequencing, including correlations between bacteria considered suboptimal, such as Gardnerella vaginalis, and metabolites enriched in term pregnancies, such as tyramine. We investigate these associations using metabolic models. We use machine learning models to predict sPTB risk from metabolite levels, weeks to months before birth, with good accuracy (area under receiver operating characteristic curve of 0.78). These models, which we validate using two external cohorts, are more accurate than microbiome-based and maternal covariates-based models (area under receiver operating characteristic curve of 0.55-0.59). Our results demonstrate the potential of vaginal metabolites as early biomarkers of sPTB and highlight exogenous exposures as potential risk factors for prematurity.
2022-11-21 | MTBLS702 | MetaboLights
Project description:<p>Preterm birth is the leading cause of neonatal morbidity and mortality. A failure to predict and understand the causes of preterm birth have limited effective interventions and therapeutics. From a cohort of 2,000 pregnant women, we performed a nested case control study on 107 well-phenotyped cases of spontaneous preterm birth (sPTB) and 432 women delivering at term. Modern and innovative Bayesian modeling of vaginal microbiota identified features of these communities associated with PTB. Seven bacterial taxa were shown to have relative abundances significantly associated with an increased risk of sPTB, with a stronger effect in African American women. However, higher vaginal levels of β-defensins significantly decreased the risk of sPTB associated with the vaginal microbiota in an ethnicity-dependent manner. These findings hold promise for the development of novel diagnostics that could more accurately identify women at risk for sPTB early in pregnancy and offer new therapeutic strategies that would include immune modulators and microbiome-based therapeutics to reduce this significant health burden.</p>
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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>
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Project description:Revealing the role of the cervico-vaginal microbiome in spontaneous preterm birth
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Project description:Revealing the role of the cervico-vaginal microbiome in spontaneous preterm birth
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Project description:Use of a probiotic supplement in maternal diet to promote a microbiome associated with decreased risk for spontaneous preterm birth. Data was acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS/MS.
2019-06-24 | MSV000084010 | GNPS
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.
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Project description:Preterm birth, defined as delivery before the 37th week of gestation, is the most common cause of neonatal mortality and the second leading cause of death in children under five years of age. Preterm birth is associated with immediate and long term morbidity as well as growth and developmental delay. Currently there is no treatment that can prevent or block preterm labor. In order to identify the molecular regulators of preterm spontaneous labor in the human myometrium, we studied the gene expression profiles of samples with Preterm Spontaneous Labour (PSL) and compared them with the gene expression profiles of samples with Preterm No Labor (PNL).
2021-04-29 | GSE134447 | GEO
Project description:Biochemistry of spontaneous preterm birth
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