Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia

• Published in: PloS one Vol. 10; no. 7; p. e0132468
• Main Authors: van Uitert, Miranda, Moerland, Perry D, Enquobahrie, Daniel A, Laivuori, Hannele, van der Post, Joris A M, Ris-Stalpers, Carrie, Afink, Gijs B
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14-07-2015; Public Library of Science (PLoS)
• Subjects: Bioinformatics; Biology; Biomarkers; Data processing; Datasets; DNA microarrays; Epidemiology; Female; Gene expression; Gene Expression Profiling - methods; Gene set enrichment analysis; Genes; Genetics; Genomics; Humans; Hypoxia; Laboratories; Meta-analysis; Mutation; Placenta; Placenta - metabolism; Pre-eclampsia; Pre-Eclampsia - genetics; Pre-Eclampsia - metabolism; Preeclampsia; Pregnancy; Protein Interaction Mapping; Proteins; Ribonucleic acid; RNA; Signal transduction; Statistical methods; Statistics; Studies; Systematic review; Target recognition; Vascular endothelial growth factor
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0132468

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.