Abstract：
BACKGROUND: Preeclampsia (PE) is a serious pregnancy-related complication caused by high blood pressure in pregnant women. The severe form has more devastating effects. According to the growing evidence, the placenta is a crucial component in the pathogenesis of PE, and eliminating it will alleviate symptoms.
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.
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.
摘要：
背景：先兆子痫（PE）是孕妇高血压引起的严重妊娠相关并发症。严重的形式具有更多的破坏性影响。根据越来越多的证据,胎盘是PE发病的重要组成部分,消除它可以缓解症状。
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log2FoldChange>0.5，包括204个过表达基因和143个低表达基因。MCC方法确定了ISG15、IFI44L、MX2,OAS2,MX1,FN1,LDHA,ITGB3,TKT,HK2基因为前十名枢纽基因。还进行了hub基因和非编码RNA之间的相互作用。最丰富的通路如下：HIF-1信号通路；癌症通路；丙氨酸，天冬氨酸和谷氨酸代谢;精氨酸生物合成;人乳头瘤病毒感染;糖酵解/糖异生;癌症中心碳代谢;缬氨酸,亮氨酸和异亮氨酸降解;半胱氨酸和蛋氨酸代谢;和半乳糖代谢。
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.
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.
