Differentially Expressed Genes in the Pre-Eclamptic Placenta: A Systematic Review and Meta-Analysis

<div><p>Objective</p><p>To systematically review the literature on human gene expression data of placental tissue in pre-eclampsia and to characterize a meta-signature of differentially expressed genes in order to identify novel putative diagnostic markers.</p><p>Data Sources</p><p>Medline through 11 February 2011 using MeSH terms and keywords related to placenta, gene expression and gene expression arrays; GEO database using the term “placent*”; and reference lists of eligible primary studies, without constraints.</p><p>Methods</p><p>From 1068 studies retrieved from the search, we included original publications that had performed gene expression array analyses of placental tissue in the third trimester and that reported on differentially expressed genes in pre-eclampsia versus normotensive controls. Two reviewers independently identified eligible studies, extracted descriptive and gene expression data and assessed study quality. Using a vote-counting method based on a comparative meta-profiling algorithm, we determined a meta-signature that characterizes the significant intersection of differentially expressed genes from the collection of independent gene signatures.</p><p>Results</p><p>We identified 33 eligible gene expression array studies of placental tissue in the 3^rd trimester comprising 30 datasets on mRNA expression and 4 datasets on microRNA expression. The pre-eclamptic placental meta-signature consisted of 40 annotated gene transcripts and 17 microRNAs. At least half of the mRNA transcripts encode a protein that is secreted from the cell and could potentially serve as a biomarker.</p><p>Conclusions</p><p>In addition to well-known and validated genes, we identified 14 transcripts not reported previously in relation to pre-eclampsia of which the majority is also expressed in the 1^st trimester placenta, and three encode a secreted protein.</p></div

Functional networks within the meta-signature.

<p>To build a functional network map the 40 meta-signature genes were analyzed using STRING software. Interactions are based on information from experimental and curated protein databases, and text mining with a high confidence setting of 0.8; the resulting networks were clustered using Markov clustering.</p

Meta signature of 4 studies on third-trimester placental tissue microRNA expression.

<p>MicroRNAs incorporated in the meta-signature are ordered by (1) the number of publications that reported the miRNA as differentially expressed and (2) alphabetically.</p>*<p>Results were inconsistent among studies, the majority of studies reported the result presented here.</p><p>–No consensus among studies: 1 study reported upregulated expression and 1 study reported downregulated expression in pre-eclampsia.</p

PRISMA flowchart summarizing the identification and selection of studies for inclusion in this systematic review.

<p>PRISMA flowchart summarizing the identification and selection of studies for inclusion in this systematic review.</p

Ingenuity Pathway Analysis identifies HIF1A as the most prominently activated upstream regulator.

<p>Thirty four out of 388 genes are direct HIF1A downstream targets according to the Ingenuity Knowledge Database. Arrows indicate the predicted relationship: orange = leads to activation (23 genes), blue = leads to inhibition (1 gene), grey = effect not predicted (9 genes), yellow = findings inconsistent with the state of downstream molecule (1 gene). Red symbols indicate genes upregulated in preeclamptic placenta, green symbols indicate genes downregulated in preeclamptic placenta. Intensity of the coloring is related to the level of up/downregulation.</p

Overlapping genes with previous meta-analyses.

<p>Venn diagram of the DEGs from the current study and the previously published studies. DEGs were extracted from the publications [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132468#pone.0132468.ref005" target="_blank">5</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132468#pone.0132468.ref006" target="_blank">6</a>] and only genes within the gene universe of our study were included in the comparison.</p

CREBBP/EP300 expression in individual studies.

<p>Forest plots for CREBBP and EP300. Squares are proportional to weights used in the meta-analysis, and the lines represent the 95% confidence interval. The diamond represents the standardized mean difference (log2 scale).</p

Volcano plot of DEGs.

<p>Volcano plot showing the standardized mean difference and the adjusted p-value for the 8,612 genes included on all platforms. The red dots represent genes differentially expressed (adjusted P<0.05) in the preeclamptic versus normotensive placenta. The symbol-marked dots indicate the five genes with the largest negative or positive standardized mean difference.</p

Studies excluded in the meta-analysis.

<p>NT = normotensive, PE = preeclampsia</p><p>^aplatform names were obtained from description in cited publication.</p><p>Studies excluded in the meta-analysis.</p

Protein interaction network analysis indicates a central role for CREBBP in the preeclamptic placenta.

<p>All 388 genes were used as input for STRING analysis and a network was built (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132468#pone.0132468.s002" target="_blank">S2 Fig</a>). Shown are the details of CREBBP interactions based on high confidence (0.8) evidence from experimental protein-protein interaction (blue lines) and curated (purple lines) databases. Proteins are indicated by nodes labeled with the encoding gene symbol. The network is enriched in interactions (p = 2.17E-13) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0132468#pone.0132468.ref030" target="_blank">30</a>].</p