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Transcriptomics-Based Subphenotyping of the Human Placenta Enabled by Weighted Correlation Network Analysis in Early-Onset Preeclampsia With and Without Fetal Growth Restriction

生物 子痫前期 胎盘 胎盘生长因子 男科 胎儿 转录组 基因表达 宫内生长受限 基因 遗传学 内科学 怀孕 医学
作者
William E. Ackerman,Catalin S. Buhimschi,Thomas L. Brown,Guomao Zhao,Taryn Summerfield,Irina Buhimschi
出处
期刊:Hypertension [Ovid Technologies (Wolters Kluwer)]
卷期号:80 (6): 1363-1374
标识
DOI:10.1161/hypertensionaha.122.20807
摘要

Background: Placental disorders contribute to pregnancy complications, including preeclampsia and fetal growth restriction (FGR), but debate regarding their specific pathobiology persists. Our objective was to apply transcriptomics with weighted gene correlation network analysis to further clarify the placental dysfunction in these conditions. Methods: We performed RNA sequencing with weighted gene correlation network analysis using human placental samples (n=30), separated into villous tissue and decidua basalis, and clinically grouped as follows: (1) early-onset preeclampsia (EOPE)+FGR (n=7); (2) normotensive, nonanomalous preterm FGR (n=5); (2) EOPE without FGR (n=8); (4) spontaneous idiopathic preterm birth (n=5) matched for gestational age; and (5) uncomplicated term births (n=5). Our data was compared with RNA sequencing data sets from public databases (GSE114691, GSE148241, and PRJEB30656; n=130 samples). Results: We identified 14 correlated gene modules in our specimens, of which most were significantly correlated with birthweight and maternal blood pressure. Of the 3 network modules consistently predictive of EOPE±FGR across data sets, we prioritized a coexpression gene group enriched for hypoxia-response and metabolic pathways for further investigation. Cluster analysis based on transcripts from this module and the glycolysis/gluconeogenesis metabolic pathway consistently distinguished a subset of EOPE±FGR samples with an expression signature suggesting modified tissue bioenergetics. We demonstrated that the expression ratios of LDHA / LDHB and PDK1 / GOT1 could be used as surrogate indices for the larger panels of genes in identifying this subgroup. Conclusions: We provide novel evidence for a molecular subphenotype consistent with a glycolytic metabolic shift that occurs more frequently but not universally in placental specimens of EOPE±FGR.
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