METHODS: GEO\'s severe preeclampsia placenta microarray datasets; GSE147776, GSE66273, GSE102897, and GSE10588, were chosen to identify differentially expressed genes (DEGs) in different biological pathways. The analysis of hub genes and related non-coding RNAs was done as well.
RESULTS: A total of 347 DEGs with adj p-value <0.05 and ǀlog2FoldChangeǀ> 0.5 were discovered between severe PEs and healthy pregnancies, including 204 over-expressed genes and 143 under-expressed genes. The MCC method identified ISG15, IFI44L, MX2, OAS2, MX1, FN1, LDHA, ITGB3, TKT, HK2 genes as the top ten hub genes. Interactions between hub genes and noncoding RNAs were also conducted. The most enriched pathways were as follows; HIF-1 signaling pathway; Pathways in cancer; Alanine, aspartate and glutamate metabolism; Arginine biosynthesis; Human papillomavirus infection; Glycolysis/Gluconeogenesis; Central carbon metabolism in cancer; Valine, leucine and isoleucine degradation; Cysteine and methionine metabolism; and Galactose metabolism.
CONCLUSIONS: This is a secondary data analysis conducted on severe preeclampsia placenta to identify differentially expressed genes, biological pathways, hub-genes, and related noncoding RNAs. Functional studies are crucial to understanding the precise role of these genes in the pathogenesis of PE. Also, accepting a gene as a diagnostic or prognostic marker for early diagnosis and management of PE requires multiple lines of evidence.
方法:GEO的重度先兆子痫胎盘微阵列数据集;选择GSE147776、GSE66273、GSE102897和GSE10588来鉴定不同生物学途径中的差异表达基因(DEGs)。同时对hub基因和相关非编码RNA进行了分析。
结果:在重度PE和健康妊娠之间共发现347个DEGs,其调整值<0.05,而
结论:这是对重度先兆子痫胎盘进行的二次数据分析,以鉴定差异表达基因,生物途径,集线器基因,和相关的非编码RNA。功能研究对于理解这些基因在PE发病机理中的确切作用至关重要。此外,接受基因作为PE早期诊断和治疗的诊断或预后标志物需要多种证据.