Combined Screening for Early Detection of Pre-Eclampsia.
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ABSTRACT:
SUBMITTER: Park HJ
PROVIDER: S-EPMC4581230 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Combined Screening for Early Detection of Pre-Eclampsia.
Park Hee Jin HJ Shim Sung Shin SS Cha Dong Hyun DH
International journal of molecular sciences 20150804 8
Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging ...[more]
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Project description:Pre-eclampsia is a common condition that affects 2-5% of pregnancies and is associated with significant maternal and perinatal morbidity, and cost to the healthcare system. In those at high risk for pre-eclampsia, interventions such as aspirin intake have been shown to reduce prevalence of disease. However, to implement these interventions, it is essential that high-risk women be identified early in pregnancy. A combined first trimester screening model for pre-eclampsia that includes maternal history, mean arterial pressure, uterine artery Doppler and PlGF has been shown to be the most effective at identifying the population at greatest risk of pre-eclampsia. This article will explore the most appropriate methods of measuring the components of first trimester screening and discuss the use of aspirin for prevention of pre-eclampsia in pregnancy.
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Project description:ObjectiveA high ratio of soluble fms-like tyrosine kinase-1 (sFlt-1) to placental growth factor (PlGF) has been linked to pre-eclampsia (PE). We evaluated the sFlt-1/PlGF ratio as a predictive marker for early-onset PE in women at risk of PE.MethodsThis prospective, Spanish, multicenter study included pregnant women with a risk factor for PE, including intrauterine growth restriction, PE, eclampsia or hemolysis, elevated liver enzymes and low platelet count syndrome in previous pregnancy, pregestational diabetes or abnormal uterine artery Doppler. The primary objective was to show that the sFlt-1/PlGF ratio at 20, 24 and 28 weeks' gestation was predictive of early-onset PE (< 34 + 0 weeks). Serum sFlt-1 and PlGF were measured at 20, 24 and 28 weeks. Multivariate logistic regression was used to develop a predictive model.ResultsA total of 819 women were enrolled, of which 729 were suitable for analysis. Of these, 78 (10.7%) women developed PE (24 early onset and 54 late onset). Median sFlt-1/PlGF ratio at 20, 24 and 28 weeks was 6.3 (interquartile range (IQR), 4.1-9.3), 4.0 (IQR, 2.6-6.3) and 3.3 (IQR, 2.0-5.9), respectively, for women who did not develop PE (controls); 14.5 (IQR, 5.5-43.7), 18.4 (IQR, 8.2-57.9) and 51.9 (IQR, 11.5-145.6) for women with early-onset PE; and 6.7 (IQR, 4.6-9.9), 4.7 (IQR, 2.8-7.2) and 6.0 (IQR, 3.8-10.5) for women with late-onset PE. Compared with early-onset PE, the sFlt-1/PlGF ratio was significantly lower in controls (P < 0.001 at each timepoint) and in women with chronic hypertension (P < 0.001 at each timepoint), gestational hypertension (P < 0.001 at each timepoint) and late-onset PE (P < 0.001 at each timepoint). A prediction model for early-onset PE was developed, which included the sFlt-1/PlGF ratio plus mean arterial pressure, being parous and previous PE, with areas under the receiver-operating characteristics curves of 0.86 (95% CI, 0.77-0.95), 0.91 (95% CI, 0.85-0.97) and 0.93 (95% CI, 0.86-0.99) at 20, 24 and 28 weeks, respectively, and was superior to models using the sFlt-1/PlGF ratio alone or uterine artery mean pulsatility index.ConclusionsThe sFlt-1/PlGF ratio can improve prediction of early-onset PE for women at risk of this condition. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.
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Project description:Background:The etiology and pathogenesis of pre-eclampsia (PE) is unclear, and there is no ideal early clinical biomarker for prediction of PE. The competing endogenous RNA (ceRNA) hypothesis is a new approach to uncover the molecular pathology of PE. The first aim of this study was to perform messenger RNA, long non-coding RNA, and circular RNA (circRNA) expression profiling of human normal and severe pre-eclampsia (SPE) placentas. circRNA, which has a stable structure, is a more suitable biomarker than other types of RNA. Therefore, the second aim of our study was to select some differentially expressed circRNAs in PE placentas as early clinical biomarkers of PE in blood circulation. Results:Using microarray analysis, we investigated differentially expressed ceRNAs in human normal and SPE placentas. Bioinformatics, such as gene ontology, KEGG pathway, and ceRNA network analyses, were performed to evaluate the microarray data and gain further insights into the biological processes. RNAs (Chd5, Furin, lnc-ELAVL4-9:1, lnc-RAP1GAP2-5:2, hsa_circ_0036877, hsa_circ_0036878, hsa_circ_0055724, hsa_circ_0049730, and hsa_circ_0036474) were validated by quantitative real-time PCR (qRT-PCR). RNA immunoprecipitation (RIP) of AGO2 in htra-8 cells and qRT-PCR analysis of hsa_circ_0036877 expression in maternal whole peripheral blood samples of participants were then conducted to confirm that hsa_circ_0036877 is a ceRNA and potential novel blood biomarker for early PE, respectively. Conclusion:Our study is the first systematic profiling of ceRNAs in placentas of PE patients and revealed the global ceRNA network integration in PE. Moreover, hsa_circ_0036877 can function as a ceRNA and serve as a potential novel blood biomarker for early PE.
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Project description:ObjectivesPreterm birth (PTB) is a major public health problem worldwide. It can occur spontaneously or be medically indicated for obstetric complications, such as pre-eclampsia (PE) or fetal growth restriction. The main objective of this study was to investigate whether there is a shared uteroplacental etiology in the first trimester of pregnancy across PTB subtypes.MethodsThis was a retrospective cohort study of singleton pregnancies that underwent screening for preterm PE as part of their routine first-trimester ultrasound assessment at a tertiary center in London, UK, between March 2018 and December 2020. Screening for preterm PE was performed using the Fetal Medicine Foundation algorithm, which includes maternal factors, mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and pregnancy-associated plasma protein-A (PAPP-A). Women with a risk of ≥ 1 in 50 for preterm PE were classified as high risk and offered prophylactic aspirin (150 mg once a day) and serial ultrasound assessments. The following delivery outcomes were evaluated: PTB < 37 weeks, iatrogenic PTB (iPTB) and spontaneous PTB (sPTB). Logistic regression analyses were performed to assess the association of PTB, iPTB and sPTB with an increased risk of preterm PE. A model for prediction of PTB < 37 weeks and < 33 weeks was developed and its performance was compared with that of an existing model in the literature.ResultsA total of 11 437 women were included in the study, of whom 475 (4.2%) had PTB. Of these, 308 (64.8%) were sPTB and 167 (35.2%) were iPTB. Patients with PTB had a higher body mass index, were more likely to be of black or Asian ethnicity, be smokers, have pregestational hypertension or diabetes, or have a history of previous PTB. They also had higher MAP (87.7 vs 86.0 mmHg, P < 0.0001), higher UtA-PI multiples of the median (MoM) (0.99 vs 0.92, P < 0.0001) and lower PAPP-A MoM (0.89 vs 1.08, P < 0.0001) compared to women with a term birth. In women at high risk of PE, the odds ratio for iPTB was 6.0 (95% CI, 4.29-8.43; P < 0.0001) and that for sPTB was 2.0 (95% CI, 1.46-2.86; P < 0.0001). A prediction model for PTB < 37 weeks and < 33 weeks, developed based on this cohort, included previous PTB, black ethnicity, chronic hypertension, diabetes mellitus, PAPP-A MoM and UtA-PI MoM. The performance of the model was similar to that of an existing first-trimester prediction model for PTB < 33 weeks (area under the curve, 0.704 (95% CI, 0.653-0.754) vs 0.694 (95% CI, 0.643-0.746)).ConclusionsIncreased first-trimester risk for uteroplacental dysfunction was associated with both iPTB and sPTB, implying a shared etiological pathway. The same factors used to predict PE risk show acceptable discrimination to predict PTB at < 33 weeks. Women at high risk of uteroplacental dysfunction may warrant additional monitoring and management for an increased risk of sPTB. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Project description:The etiology of preeclampsia, a hypertensive disorder of human pregnancy, remains unknown. We addressed fetal sex selection and the suggestive role of fetal HLA-G and related genes, regulating maternal immune responses, in preeclampsia pathogenesis. We assessed birth sex ratios, weights, and seasonality of preeclampsia among 1.79 million births in Finland. We studied haplotypes of HLA-G 3’ untranslated region (UTR), regulating HLA-G expression, in 1000 Genomes series and in a preeclampsia cohort (n=1249). We quantified placental (n=163) mRNA expression of 136 genes, studied HLA-G and IFNα protein expression by immunohistochemistry, and measured maternal and fetal circulating IFNα levels by ELISA. Population-level data showed loss of male fetuses as a characteristic of preeclampsia. As a potential contributor to immune-mediated loss, we found balancing selection at HLA-G 3’UTR modulating sex ratio, and association of HLA-G 3’UTR haplotypes with placental HLA-G expression. HLA-G and its receptors were downregulated in preeclampsia placentas, and surprisingly, interferon alpha-1 (IFNA1) was highly upregulated. IFNA1 and HLA-G distinguished preeclampsia better than placental FLT1 expression. Fetal but not maternal circulating IFNα, produced by trophoblasts, showed association with maternal hypertension and fetal growth restriction. We uncover the link between placental HLA-G expression and human birth sex ratio. We propose that preeclampsia shares, through reduced HLA-G mediated immunotolerance, the mechanism needed to fight placental viral infections and malaria in evolution. IFNα upregulation in preeclampsia placenta, together with its known actions upstream of inflammatory genes, encourages testing IFNα inhibitors and especially the pregnancy-approved antimalarial hydroxichloroquine in treatment of preeclampsia.
2019-11-25 | GSE125460 | GEO
Project description:IntroductionPre-eclampsia (PE) is a leading cause of perinatal morbidity and mortality worldwide. Low-dose aspirin can prevent PE in high risk pregnancies if started early. However, despite intense research into the area, early pregnancy screening for PE risk is still not a routine part of pregnancy care. Several studies have described the application of artificial intelligence (AI) and machine learning (ML) in risk prediction of PE and its subtypes. A systematic review of available literature is necessary to catalogue the current applications of AI/ML methods in early pregnancy screening for PE, in order to better inform the development of clinically relevant risk prediction algorithms which will enable timely intervention and the development of new treatment strategies. The aim of this systematic review is to identify and assess studies regarding the application of AI/ML methods in early pregnancy screening for PE.MethodsA systematic review of peer-reviewed as well as the pre-published cohort, case-control, or cross-sectional studies will be conducted. Relevant information will be accessed from the following databases; PubMed, Google Scholar, Scopus, Embase, Web of Science, Cochrane Library, Arxiv, BioRxiv, and MedRxiv. The studies will be evaluated by two reviewers in a parallel, blind assessment of the literature, a third reviewer will assess any studies in which the first two reviewers did not agree. The free online tool Rayyan, will be used in this literature assessment stage. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist will be used to guide the review process and the methods of the studies will be assessed using the Newcastle-Ottawa scale. Narrative synthesis will be conducted for all included studies. Meta-analysis will also be conducted where data quality and availability allow.Ethics and disseminationThe review will not require ethical approval and the findings will be published in a peer-reviewed journal using the PRISMA guidelines.Trial registrationTrial registration: The protocol for this systematic review has been registered in PROSPERO [CRD42022345786]. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022345786.
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Project description:BackgroundPre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point.ResultsThe use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia].ConclusionsFor pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.
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Project description:Background: Preeclampsia (PE) is a multi-systemic maternal syndrome with substantial maternal and fetal morbidity and mortality. Currently, there is no clinically viable non-invasive biomarker assay for early detection, thus limiting the effective prevention and therapeutic strategies for PE. Methods: We conducted a discovery-training-validation three-phase retrospective and prospective study with cross-platform and multicenter cohorts. The initial biomarkers were discovered and verified in tissue specimens by small RNA sequencing and qRT-PCR. A miRNA signature (miR2PE-score) was developed using the Firth’s bias-reduced logistic regression analysis, and subsequently validated in two independent multinational retrospective cohorts and two prospective plasma cohorts. Results: We initially identified five PE-associated differentially expressed miRNAs from miRNA sequencing data and subsequently validated two miRNAs (miR-196b-5p and miR-584-5p) as robust biomarkers by association analysis with clinical characteristics and qRT-PCR in tissue specimens in the discovery phase. Using the Firth’s bias-reduced logistic regression analysis, we developed the miR2PE-score for the early detection of PE. The miR2PE-score showed a high diagnostic performance with an area under the receiver operating characteristic curve (AUROC) of 0.920, 0.848, 0.864 and 0.812 in training, internal and two external validation cross-platform and multicenter cohorts, respectively. Finally, we demonstrated the non-invasive diagnostic performance of the miR2PE-score in two prospective plasma cohorts with AUROC of 0.933 and 0.787. Furthermore, the miR2PE-score revealed superior performance in non-invasive diagnosis compared with previously published miRNA biomarkers. Conclusions: We developed and validated a novel and robust blood-based miRNA signature, which may serve as a promising clinically applicable non-invasive tool for the early detection of PE.
2022-09-21 | GSE206988 | GEO
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