Differential placental gene expression in preeclampsia

Abstract

Objective: Candidate genes that are associated with preeclampsia have not been described fully. We conducted microarray and confirmatory quantitative real time polymerase chain reaction studies to investigate global placental gene expression in preeclampsia.

Study design: RNA was extracted from placental samples that were collected from 18 preeclampsia cases and 18 normotensive control subjects. Oligonucleotide probes that represented 22,000 genes were used to measure gene expression in each sample. Differential gene expression was evaluated with the Student t test, fold change assessment, and significance analysis of microarrays. Functions and functional relationships of differentially expressed genes were evaluated.

Results: Genes (n = 58) that participated in immune system, inflammation, oxidative stress, signaling, growth, and development pathways were expressed differentially in preeclampsia. These genes included previously described candidate genes (such as leptin), potential candidate genes with related functions (such as CYP11A) and novel genes (such as CDKN1C).

Conclusion: Expression of genes (both candidate and novel) with diverse functions is associated with preeclampsia risk, which reflects the complex pathogenesis.

Figure 1. Volcano plot of placental gene expression

Distribution of Students’ t-test p-value (y-axis: -ln [p-value]) and fold change (x-axis: ln[fold change]) results comparing placental gene expressions of preeclampsia cases and controls. All genes are shown in blue while those genes that are differentially expressed in evaluations using at least two of the following; Student’s T-test p-value > 0.05, absolute fold change ≥ 1.5 and/or false discovery rate in SAM analysis < 10%, are shown in purple.

Figure 2. Venn diagram summary of distribution of differentially expressed genes

Circles represent numbers of differentially expressed genes comparing preclamptic placenta with normotensive placenta using Students’ t-test p-value < 0.05 (light blue), fold change > 1.5 (light purple) and SAM false discovery rate < 10% (light green). Numbers within circles represent total number of genes and numbers of either up-regulated (↑) or down-regulated (↓) genes. The intersections of the circles represent the number of genes differentially expressed using two or greater than two criteria as defined above.

Figure 3. Heat map illustration of phylogenetic tree of samples and selected differentially selected genes

The genes (rows) and participants (columns) were grouped according to level and nature of gene expression and subjected to hierarchical tree clustering. The color code for signal strength in the classification scheme is as follows; induced genes are indicated by shades of red while repressed genes are indicated by shades of green. Gray represents absent data.

Figure 4. Pathway networks identified using Ingenuity Pathway Analysis

The networks were generated through the use of Ingenuity Pathways Analysis (Ingenuity® Systems, www.ingenuity.com). Each gene identifier was mapped to its corresponding gene object in the Ingenuity Pathways Knowledge Base (IPKB) and overlaid onto a global molecular network developed from information contained in the IPKB. Colored genes are genes in our set of differentially expressed genes (pink=upregulated and green=down regulated).

Figure 5. Comparison of microarray and QRT-PCR expression measurements

Box plots describing distributions of microarray and QRT-PCR expression measurements of selected genes among cases and controls.