Dataset Information

Prevention of preeclampsia.

ABSTRACT: Preeclampsia is a common complication of pregnancy that is associated with an increased risk of maternal and neonatal morbidity and mortality. Currently, delivery is the only cure for preeclampsia; therefore, effective prevention and treatment options for this condition are sorely needed. In the current issue of the JCI, Mirzakhani et al. report the findings of the Vitamin D Antenatal Asthma Reduction Trial (VDAART), a well-conducted large, randomized, double-blind, placebo-controlled trial of vitamin D supplementation for the prevention of preeclampsia. Though vitamin D supplementation had no effect on the risk of preeclampsia, reduced maternal serum vitamin D levels did correlate with preeclampsia risk. Mirzakhani and colleagues identified a number of gene pathways that are differentially regulated among women with low serum vitamin D levels who develop preeclampsia. These results indicate that further research on the role of vitamin D in preeclampsia is warranted.

SUBMITTER: Grotegut CA

PROVIDER: S-EPMC5127661 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Prevention of preeclampsia.

Grotegut Chad A CA

The Journal of clinical investigation 20161114 12

Preeclampsia is a common complication of pregnancy that is associated with an increased risk of maternal and neonatal morbidity and mortality. Currently, delivery is the only cure for preeclampsia; therefore, effective prevention and treatment options for this condition are sorely needed. In the current issue of the JCI, Mirzakhani et al. report the findings of the Vitamin D Antenatal Asthma Reduction Trial (VDAART), a well-conducted large, randomized, double-blind, placebo-controlled trial of v ...[more]

PMID: 27841760

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Project description:ObjectivePreeclampsia (PE) is a pregnancy-specific multisystem disease as well as an important cause of maternal and perinatal death. This study aimed to analyze the placental transcriptional data and clinical information of PE patients available in the published database and predict the target genes for prevention of PE.MethodsThe clinical information and corresponding RNA data of PE patients were downloaded from the GEO database. Cluster analysis was performed to examine the correlation between different genotyping genes and clinical manifestations. Then, bioinformatic approaches including GO, KEGG, WGCNA, and GSEA were employed to functionally characterize candidate target genes involved in pathogenesis of PE.ResultsTwo PE datasets GSE60438 and GSE75010 were obtained and combined, thereby providing the data of 205 samples in total (100 non-PE and 105 PE samples). After eliminating the batch effect, we grouped and analyzed the integrated data, and further performed GSEA analysis. It was found that the genes in group 1 and group 2 were different from those in normal samples. Moreover, WGCNA analysis revealed that genes in group 1 were up-regulated in turquoise module, including SASH1, PIK3CB and FLT-1, while genes in group 2 were up-regulated in the blue and brown modules. We further conducted GO and KEGG pathway enrichment analyses and found that the differential genes in turquoise module were mainly involved in biological processes such as small molecular catabolic process, while being highly enriched in pathways, including MAPK signaling pathway and Rap1 signaling pathway.ConclusionFLT-1 was conventionally used to predict PE risk, and sFLT-1 could also be used as an indicator to evaluate PE treatment effect. As a candidate biomarker for predicting PE, SASH1 may participate in proliferation, migration, invasion and epithelial mesenchymal transformation of human trophoblast cells by regulating MAPK pathway and Rap1 signaling pathway, thus affecting the progression of PE. The mechanism allowing PIK3CB to regulate PE development was not clear, while the gene could be another candidate biomarker for PE risk prediction. This is an exploratory study and our findings were still required verification in further studies.

Project description:ObjectivesPreeclampsia is divided into early-onset (delivery before 34 weeks of gestation) and late-onset (delivery at or after 34 weeks) subtypes, which may rise from different etiopathogenic backgrounds. Early-onset disease is associated with placental dysfunction. Late-onset disease develops predominantly due to metabolic disturbances, obesity, diabetes, lipid dysfunction, and inflammation, which affect endothelial function. Our aim was to use cluster analysis to investigate clinical factors predicting the onset and severity of preeclampsia in a cohort of women with known clinical risk factors.MethodsWe recruited 903 pregnant women with risk factors for preeclampsia at gestational weeks 12+0-13+6. Each individual outcome diagnosis was independently verified from medical records. We applied a Bayesian clustering algorithm to classify the study participants to clusters based on their particular risk factor combination. For each cluster, we computed the risk ratio of each disease outcome, relative to the risk in the general population.ResultsThe risk of preeclampsia increased exponentially with respect to the number of risk factors. Our analysis revealed 25 number of clusters. Preeclampsia in a previous pregnancy (n = 138) increased the risk of preeclampsia 8.1 fold (95% confidence interval (CI) 5.7-11.2) compared to a general population of pregnant women. Having a small for gestational age infant (n = 57) in a previous pregnancy increased the risk of early-onset preeclampsia 17.5 fold (95%CI 2.1-60.5). Cluster of those two risk factors together (n = 21) increased the risk of severe preeclampsia to 23.8-fold (95%CI 5.1-60.6), intermediate onset (delivery between 34+0-36+6 weeks of gestation) to 25.1-fold (95%CI 3.1-79.9) and preterm preeclampsia (delivery before 37+0 weeks of gestation) to 16.4-fold (95%CI 2.0-52.4). Body mass index over 30 kg/m2 (n = 228) as a sole risk factor increased the risk of preeclampsia to 2.1-fold (95%CI 1.1-3.6). Together with preeclampsia in an earlier pregnancy the risk increased to 11.4 (95%CI 4.5-20.9). Chronic hypertension (n = 60) increased the risk of preeclampsia 5.3-fold (95%CI 2.4-9.8), of severe preeclampsia 22.2-fold (95%CI 9.9-41.0), and risk of early-onset preeclampsia 16.7-fold (95%CI 2.0-57.6). If a woman had chronic hypertension combined with obesity, gestational diabetes and earlier preeclampsia, the risk of term preeclampsia increased 4.8-fold (95%CI 0.1-21.7). Women with type 1 diabetes mellitus had a high risk of all subgroups of preeclampsia.ConclusionThe risk of preeclampsia increases exponentially with respect to the number of risk factors. Early-onset preeclampsia and severe preeclampsia have different risk profile from term preeclampsia.

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Prevention of preeclampsia.

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Prevention of preeclampsia.

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