Extracellular microRNA Biomarkers for Diagnostic and Prognostic Assessment of Preeclampsia at Triage
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PROVIDER: PRJNA916338 | ENA |
REPOSITORIES: ENA
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Project description:Extracellular microRNA Biomarkers for Diagnostic and Prognostic Assessment of Preeclampsia at Triage
| PRJNA916339 | ENA
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia.
2014-05-14 | GSE48424 | GEO
Project description:Background: Preeclampsia (PE) is a placental disease characterized by hypertension and proteinuria in pregnant women, which is associated with a high maternal and infantile morbidity. However, circulating biomarkers able to predict the prognosis of PE are lacking. Methods: Thirty-eight women were included in the study. They consisted of 19 patients with PE (13 with severe PE and 6 women with non-severe PE) and 19 gestational age-matched normal pregnancy controls. We measured coagulation pathway, endothelial responses and microparticle release and circulating gene expression in PE patient groups and normotensive controls. Results: The measurement of markers associated with coagulation pathway, endothelial activation and circulating microparticles enabled to discriminate PE from normal pregnancy but were not sufficient to distinguish severe from non-severe PE. PE patients also exhibited a specific transcriptional program distinct from that of control women and subtle differences were observed between severe and non-severe PE. Functional annotation of the up-modulated signature in PE highlighted two main functions related to ribosome and complement. Importantly, we found that 8 genes were specifically up-modulated in severe preeclampsia. Among these genes, the expression of VSIG4 was significantly increased in patients with severe preeclampsia in comparison with controls and patients with non-severe preeclampsia. Conclusion: Using transcriptional signatures of blood samples, we identified the gene encoding the estrogen receptor as a potential diagnostic marker of severe preeclampsia. In addition, the determination of this gene may improve the prognostic assessment of severe preeclampsia. Thirty-eight women were included in the study: 19 patients with PE, including 6 women with non-severe PE and 13 with severe PE, and 19 women with normal pregnancy (NP) selected according to age, weight, smoking status, race, gestational age at the inclusion, and blood pH (Table 1 of manuscript). Women with NP had no history of medical illness or medication, and received routing prenatal care. The diagnostic of PE was based on a blood pressure of M-bM-^IM-% 140/90 mmHg taken twice, uricemia above normal laboratory range (120-420 M-BM-5mol/L), and proteinuria higher than 300 mg in a 24 hour-collection, occurring after 20 gestational weeks in previously normotensive women (Table 2). The criteria used to define severe PE included one of the following conditions: a blood pressure higher than 160/110 mmHg, a proteinuria higher than 1500 mg/24h), a multisystem disorder, maternal cerebral symptoms (seizures, stroke) or intrauterine growth restriction below the 3M-BM-0 percentile. Women with multiple gestations, fetal congenital malformations/chromosomal abnormalities, recent infection, antiphospholipid antibodies, trauma, drug or alcohol abuse during pregnancy, preexisting hypertension, thrombophilia with PE history, or women receiving anticoagulant or antiaggregation therapy were excluded from the study. Two microarrays (one non-severe PE and one normal) were discarded from the analysis for technical reasons. Thus, only 36 microarrays are included here.
2014-05-14 | E-GEOD-48424 | biostudies-arrayexpress
Project description:Diagnostic and prognostic biomarkers associated with histotype in advanced epithelial ovarian cancer
| PRJNA1254600 | ENA
Project description:Despite advances in cancer treatments, epithelial ovarian cancer (EOC) remains the leading cause of death among gynecologic cancers. EOC is stratified into five main histopathological subtypes: high-grade serous carcinoma (HGSC), clear cell carcinoma (CCC), mucinous carcinoma (MC), endometrioid carcinoma (EC), and low-grade serous carcinoma (LGSC). However, personalized treatment strategies and reliable biomarkers for all histotypes remain elusive. Building on our previous work with early-stage EOC, we aim to explore diagnostic and prognostic biomarkers in advanced-stage EOC, updated to the latest World Health Organization classification guidelines from 2020, using comprehensive transcriptomic profiling from total RNA sequencing of 146 EOC patients. Differential expression analysis identified top 9 histotype-specific gene panels for HGSC, CCC, MC, and EC, including S100A1 (HGSC), ARID3A (CCC), LGALS4 (MC), and SCUBE2 (EC). We also identified gene candidates associated with overall survival and disease-specific survival, reflecting both favorable (e.g., OTOF, EEF1E1-BLOC1S5, and STAC3) and unfavorable (e.g., SMOC1, GDPGP1, EPRS1) clinical outcome. Additionally, enrichment analysis revealed tumor progression-related pathways unique to each histotype, offering insights into molecular mechanisms underlying disease progression and potential therapeutic targets. These findings provide valuable insights into the molecular landscape of advanced-stage EOC, paving the way for more effective diagnostic and prognostic tools across diverse histotypes.
2025-10-01 | GSE295399 | GEO
Project description:Early diagnosis of acute community-acquired pneumonia (CAP) is important in patient triage and treatment decisions. To identify biomarkers that distinguish patients with CAP from non-CAP controls, we conducted an untargeted global metabolome analysis for plasma samples from142 patients with CAP (CAP cases) and 97 without CAP (non-CAP controls). Thirteen lipid metabolites could discriminate between CAP cases and non-CAP controls with area-under-the-receiver-operating-characteristic curve of > 8 (P ≤ 10-9). The levels of glycosphingolipids, sphingomyelins, lysophosphatidylcholines and L-palmitoylcarnitine were higher, while the levels of lysophosphatidylethanolamines were lower in the CAP cases than those in non-CAP controls. All 13 metabolites could distinguish CAP cases from the non-infection, extrapulmonary infection and non-CAP respiratory tract infection subgroups. The levels of trihexosylceramide (d18:1/16:0) were higher, while the levels of lysophosphatidylethanolamines were lower, in the fatal than those of non-fatal CAP cases. Our findings suggest that lipid metabolites are potential diagnostic and prognostic biomarkers for CAP.
2016-08-11 | MTBLS354 | MetaboLights
Project description:Novel prognostic biomarkers in central neurocytoma
| PRJNA1216957 | ENA
Project description:Preterm birth has dramatically increased within the population (i.e., >10%) and preeclampsia is one of the most unanticipated sub-categories of preterm birth. No clinical parameter or biomarkers exists for preeclampsia preterm birth, except for high blood pressure toward the end of pregnancy. The current study investigates the potential use of epigenetic (DNA methylation) alterations as a preeclampsia biomarker. Non-preeclampsia term births were compared to preeclampsia preterm births to identify methylation differences. Buccal cell cheek swabs were used as a marker cell for systemic epigenetic alterations in the individuals. A total of 389 differential DNA methylation regions (DMRs) were identified and associated with the presence of preeclampsia. The DMRs were genome-wide and were predominantly low CpG density (<2 CpG/100 bp). In comparison with a previous preterm birth epigenetic biomarker there was a 15% (60 DMR) overlap, indicating the majority of the DMRs are unique for preeclampsia.
2025-04-22 | GSE259360 | GEO
Project description:The use of plasma microRNAs (miRs) as diagnostic and prognostic biomarkers of chronic kidney disease (CKD)
| PRJNA1091676 | ENA
Project description:This data set is downloaded from MetaboLights (http://www.ebi.ac.uk/metabolights/) accession number MTBLS354 Abstract:Early diagnosis of acute community-acquired pneumonia (CAP) is important in patient triage and treatment decisions. To identify biomarkers that distinguish patients with CAP from non-CAP controls, we conducted an untargeted global metabolome analysis for plasma samples from142 patients with CAP (CAP cases) and 97 without CAP (non-CAP controls). Thirteen lipid metabolites could discriminate between CAP cases and non-CAP controls with area-under-the-receiver-operating-characteristic curve of > 8 (P ? 10-9). The levels of glycosphingolipids, sphingomyelins, lysophosphatidylcholines and L-palmitoylcarnitine were higher, while the levels of lysophosphatidylethanolamines were lower in the CAP cases than those in non-CAP controls. All 13 metabolites could distinguish CAP cases from the non-infection, extrapulmonary infection and non-CAP respiratory tract infection subgroups. The levels of trihexosylceramide (d18:1/16:0) were higher, while the levels of lysophosphatidylethanolamines were lower, in the fatal than those of non-fatal CAP cases. Our ?ndings suggest that lipid metabolites are potential diagnostic and prognostic biomarkers for CAP.
2017-04-16 | MSV000080957 | GNPS