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Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes [WGBS]

ABSTRACT: Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. Here we investigated cell-free DNA and RNA content of 102 maternal and 25 cord plasma samples. Employing a novel deconvolution methodology, we found that during the first trimester, placenta-specific DNA increased prior to the subsequent development of gestational diabetes with no change in patients with preeclampsia while decreasing with maternal obesity. Moreover, using cell-free RNA sequencing, APOs revealed seventy-one differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3 and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.

ORGANISM(S): Homo sapiens

PROVIDER: GSE154348 | GEO | 2020/10/19

REPOSITORIES: GEO

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Project description:Background: Long non-coding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of diseases. We want to study the lncRNAs profiles in preeclampsia. Preeclampsia has been observed in patients with molar pregnancy where a fetus is absent demonstrating that the placenta is sufficient to cause the condition. So we analyze the lncRNAs profiles in preeclampsia placentas. In this study, we described the lncRNAs profiles in 6 preeclampsia placentas (T) and 5 matched normal pregnancy placentas (N) tissues by microarray. Methodology/Principal Findings: With abundant and varied probes accounting 33,045 LncRNAs in our microarray, the number of lncRNAs that expressed at a certain level could be detected is 28,443. From the data we found there were 738 lncRNAs that differentially expressed (M-bM-^IM-%1.5 fold-change) among preeclampsia placentas compared with matched controls. Up to 18,063 coding transcripts could be detected in placenta samples through 30,215 coding transcripts probes. Coding-non-coding gene co-expression networks (CNC network) were constructed based on the correlation analysis between the differential expressed lncRNAs and mRNAs. According to the GO-Pathway analysis of differential expressed lncRNAs/mRNAs, we choose three lncRNAs to analyze the relationship between lncRNAs and preeclampsia. LOC391533, LOC284100, CEACAMP8 were evaluated by qPCR in 40 of preeclampsia placentas and 40 of controls. The results showed three lncRNAs were aberrantly expressed in preeclampsia placentas compared with controls. Conclusions/Significance: Our study is the first one to determine genome-wide lncRNAs expression patterns in preeclampsia placenta by microarray. The results displayed that clusters of lncRNAs were aberrantly expressed in preeclampsia placenta compared with controls, which revealed that lncRNAs differentially expressed in preeclampsia placenta may exert a partial or key role in preeclampsia development. Misregulation of LOC391533, LOC284100, CEACAMP8 might be associated with preeclampsia. Taken together, this study may provide potential targets for future treatment of preeclampsia and novel insights into preeclampsia biology. LncRNAs/mRNAs profiles in 6 preeclampsia placentas and 5 matched normal pregnancy placentas tissues by microarray using Arraystar v2.0.

Project description:Data on the temporal dynamics of human placental gene expression is scarce. We have completed the first whole-genome profiling of human placental gene expression dynamics (GeneChips, Affymetrix®) from early to mid- gestation (10 samples; gestational weeks 5 to 18) and report 154 genes with considerable change in transcript levels (FDR P<0.1). Functional enrichment analysis revealed >200 GO categories that are statistically over-represented among 105 genes with dynamically increasing transcript levels. Analysis in an extended sample (n=43; gestational weeks 5 to 41) conformed a highly significant (FDR P<0.05) expressional peak in mid-gestation placenta for ten genes: BMP5, CCNG2, CDH11, FST, GATM, GPR183, ITGBL1, PLAGL1, SLC16A10, STC1. A central hypothesis of our study states that the aberrant expression of genes characteristic to mid-gestation placenta may contribute to affected fetal growth, maternal preeclampsia (PE) or gestational diabetes (GD). The gene STC1 coding for Stanniocalcin 1 (STC1) was identified with a sharp placental expressional peak in mid-gestation, increased mRNA levels at term and significantly elevated STC1 protein levels in post-partum maternal plasma in all pregnancy complications. The highest STC1 levels were identified in women, who developed simultaneously PE and delivered an SGA baby (median 731 vs 418 pg/ml in controls; P=0.001). CCNG2 and LYPD6 exhibited significantly increased placental mRNA expression and enhanced intensity of immunohistochemistry staining in placental sections all studied in GD and PE cases. Aberrant expression of mid-gestation specific genes in pregnancy complications at term indicates the importance of the fine-scale tuning of the temporal dynamics of transcription regulation in placenta. Observed significantly elevated plasma STC1 in complicated pregnancies warrants further investigations of its potential as a biomarker. Interestingly, a majority of genes with high expression in mid-gestation placenta have also been implicated in adult complex disease. This observation promotes a recently opened discussion on the role of placenta in developmental programming. 4 samples; this submission is extension of our earlier study (accession GSE22490).

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Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes [WGBS]

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