Bioinformatics identification of potential genes and pathways in preeclampsia based on functional gene set enrichment analyses.

Bioinformatics identification of potential genes and pathways in preeclampsia based on functional gene set enrichment analyses. Exp Ther Med. 2019 Sep;18(3):1837-1844 Authors: Li X, Fang Y Abstract Preeclampsia is a complication of pregnancy characterized by new-onset hypertension and proteinuria of gestation, with serious consequences for mother and infant. Although a vast amount of research has been performed on the pathogenesis of preeclampsia, the underlying mechanisms of this multisystemic disease have remained to be fully elucidated. Data were retrieved from Gene Expression Omnibus database GSE40182 dataset. After data preprocessing, differentially expressed genes of placental cells cultured in vitro from preeclampsia and normal pregnancy were determined and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify the associated pathways. Furthermore, functional principal component analysis (FPCA) was used to calculate the corresponding F-value of each gene. In order to further study the key signaling pathways of preeclampsia, an elastic-net regression model and the Mann-Whitney U (MWU) test were used to estimate the weight of the signaling pathways. Finally, a co-expression network was generated and hub genes were identified based on the topological features. A total of 134 pathways with a role in preeclampsia were identified. The gene expression data of placenta cells cultured in vitro for different durations wer...
Source: Experimental and Therapeutic Medicine - Category: General Medicine Tags: Exp Ther Med Source Type: research

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