Abstract
One in five pregnant women suffer from gestational complications, prevalently driven by placental malfunction. Using RNASeq, we analyzed differential placental gene expression in cases of normal gestation, late-onset preeclampsia (LO-PE), gestational diabetes (GD) and pregnancies ending with the birth of small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns (n = 8/group). In all groups, the highest expression was detected for small noncoding RNAs and genes specifically implicated in placental function and hormonal regulation. The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes. Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results. A limited number of transcription factors including LRF, SP1 and AP2 were identified as possible drivers of these changes. Notable differences were detected in differential expression signatures of LO-PE subtypes defined by the presence or absence of intrauterine growth restriction (IUGR). LO-PE with IUGR showed higher correlation with SGA and LO-PE without IUGR with LGA placentas. Whereas changes in placental transcriptome in SGA, LGA and GD cases were less prominent, the overall profiles of expressional disturbances overlapped among pregnancy complications providing support to shared placental responses. The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.
Highlights
Common disorders concerning up to 20% of all gestations, the explicit understanding of gene expression signatures of the malfunctioning placenta is crucial to pinpoint critically involved genes and mechanisms, and to discover novel biomarkers and therapeutic targets for early prediction and clinical management
The study profiles placental differential gene expression signatures in prevalent adverse pregnancy outcomes at term, focusing on maternal late-onset preeclampsia (LO-PE), gestational diabetes (GD), and pregnancies ending with the birth of either small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns
To characterize the placental transcriptome profile in normal compared to complicated pregnancies, we performed RNA sequencing (RNA-Seq) for 40 placental samples taken at delivery and covering multiple well-defined pregnancy outcomes at term
Summary
Common disorders concerning up to 20% of all gestations, the explicit understanding of gene expression signatures of the malfunctioning placenta is crucial to pinpoint critically involved genes and mechanisms, and to discover novel biomarkers and therapeutic targets for early prediction and clinical management. More placental gene expression data is available from microarray-based experiments[14], but these projects have focused mostly on a specific gestational complication, predominantly preeclampsia. There is still an open question, whether each pregnancy complication is characterized by distinct aberrant placental gene expression profiles or whether gestational disturbances share common molecular signatures reflecting overall impaired implantation, placental development and function. We aimed at a comprehensive and systematic analysis of placental transcriptomes of 40 samples over a broad range of pregnancy outcomes, utilizing the most up-to-date methodology, RNA-Seq. The study profiles placental differential gene expression signatures in prevalent adverse pregnancy outcomes at term, focusing on maternal late-onset preeclampsia (LO-PE), gestational diabetes (GD), and pregnancies ending with the birth of either small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns. The study data represent a rich catalogue for potential biomarkers and therapeutic targets
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