Ontology highlight
ABSTRACT:
PROVIDER: PRJNA430710 | ENA |
REPOSITORIES: ENA
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Project description:Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. We investigated the cell-free RNA content of 102 maternal, 25 cord plasma samples and 7 non pregnant women as control. using cell-free RNA sequencing, APOs revealed seventy-one differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3 and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.
2020-10-19 | GSE154377 | GEO
Project description:Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. Here we investigated cell-free DNA and RNA content of 102 maternal and 25 cord plasma samples. Employing a novel deconvolution methodology, we found that during the first trimester, placenta-specific DNA increased prior to the subsequent development of gestational diabetes with no change in patients with preeclampsia while decreasing with maternal obesity. Moreover, using cell-free RNA sequencing, APOs revealed seventy-one differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3 and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.
2020-10-19 | GSE154348 | GEO
Project description:Cell-free RNAs in biofluids provide opportunities to monitor cancer in a non-invasive manner. Although extracellular microRNAs are extensively characterized, fragmented cell-free long RNAs are not well investigated. Here, we developed Detector-seq (depletion-assisted multiplexing cell-free total RNA sequencing) to enable the deciphering of the cell-free transcriptome. After demonstrating the superior performance of detecting fragmented cell-free long RNAs, we applied Detector-seq to compare cell-free RNAs in human plasma and its extracellular vesicle (EV). Distinct human and microbial RNA signatures were revealed. Structured circular RNA, tRNA, and Y RNA were enriched in plasma, while mRNA and srpRNA were enriched in EV. Meanwhile, cell-free RNAs derived from the virus were more enriched in plasma than in EV. We identified RNAs that showed a selective distribution between plasma and EV and uncovered their distinct functional pathways, that is RNA splicing, antimicrobial humoral response enriched in plasma and transcriptional activity, cell migration, and antigen receptor-mediated immune signals enriched in EV. Although distinctive cancer-relevant RNA signals were identified in plasma and EV, a comparable performance of distinguishing cancer patients from normal individuals could be achieved. Compared to human RNAs, microbe-derived RNA features enabled better classification between colorectal and lung cancer. And for these microbial RNAs, plasma RNAs outperformed EV RNAs for the discrimination of cancer types. Overall, our work provides insights into the unexplored difference of cell-free RNA signals between plasma and EV, thus offering practical guidance for proper selection (with/without EV enrichment) when launching an RNA-based liquid biopsy study. Furthermore, with the ability to capture understudied cell-free long RNA fragments, Detector-seq offers new possibilities for transcriptome-wide characterization of cell-free RNAs to facilitate the understanding of extracellular RNA biology and clinical advances of liquid biopsy.
2024-03-27 | GSE216561 | GEO
Project description:Purpose: Sequencing analysis of plasma cell-free RNA was performed to study the effects of space flight and microgravity environment in mice. Methods: Plasma samples were collected during the JAXA MHU-1 mission as reported previously (Shiba et al., 2017, Scientific Reports). Total RNA was purified from plasma samples and processed for sequencing analysis, to compare RNA expression profiles in ground control, space flight and artificial 1-G control groups.
2022-11-16 | GSE213808 | GEO
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:Plasma cell-free RNA profiling distinguishes cancer from pre-malignant conditions
| PRJNA758012 | ENA
Project description:Cell-free RNA (cfRNA) in plasma reflects gene expression profiles of both localized sites of cancer and at the systemic host response. Here we explore the diagnostic potential of cell-free transcriptomes by mRNA sequencing. We sequenced total cell-free plasma RNA from 90 plasma samples from two independent sample cohorts representing two cancer types, two pre-cancerous conditions and non-cancer donors. We identified distinct gene sets and built classification models that could distinguish cancer patients with specific cancer types from premalignant conditions and non-cancer individuals with high accuracy. Determination of multiple myeloma from its pre-cancerous monoclonal gammopathy of undetermined significance (MGUS) yielded an accuracy of 90% (17/19). Detection of primary liver cancer from its premalignant condition cirrhosis yielded an accuracy of 100% (12/12). This work lays the foundation for developing low cost assays by measuring mRNA transcript levels in plasma using a small panel of genes for detection that can distinguish the presence of cancer from pre-cancerous conditions and non-cancer individuals.
2022-04-25 | GSE182824 | GEO