Integrated analysis of multiple microarray studies to identify potential pathogenic gene modules in preeclampsia

Abstract Background Preeclampsia is a life-threatening hypertensive disorder during pregnancy, while underlying pathogenesis and its diagnosis are incomplete. Methods In this study, we utilized the Robust Rank Aggregation method to integrate 6 eligible preeclampsia microarray datasets from Gene Expression Omnibus database. We used linear regression to assess the associations between significant differentially expressed genes (DEGs) and blood pressure. Functional annotation, protein–protein interaction, Gene Set Enrichment Analysis (GSEA) and single sample GSEA were employed for investigating underlying pathogenesis in preeclampsia. Results We filtered 52 DEGs and further screened for 5 hub genes (leptin, pappalysin 2, endoglin, fms related receptor tyrosine kinase 1, tripartite motif containing 24) that were positively correlated with both systolic blood pressure and diastolic blood pressure. Receiver operating characteristic indicated that hub genes were potential biomarkers for diagnosis and prognosis in preeclampsia. GSEA for single hub gene revealed that they were all closely related to angiogenesis and estrogen response in preeclampsia. Moreover, single sample GSEA showed that the expression levels of 5 hub genes were correlated with those of immune cells in immunologic microenvironment at maternal-fetal interface. Conclusions These findings provide new insights into underlying pathogenesis in preeclampsia; 5 hub genes were identified as biomarkers for diagnosis and prognosis in preeclampsia.