Pre-eclampsia is one of the most serious pregnancy-associated disorders, and is defined by hypertension (systolic blood pressure higher than 140mmHg or diastolic blood pressure higher than 90mmHg) with proteinuria (more than 0.3g/day). It is not a simple complication of pregnancy, but is rather a syndrome of multiple organ failure involving the liver, kidney, and lung, as well as coagulatory and neural systems. There is now an emerging consensus that pre-eclampsia is a complex polygenetic trait in which maternal and fetal genes, as well as environmental factors, are involved, although the precise mechanism of the disorder has remained elusive. In this study, we have performed gene expression profiling to further elucidate the mechanisms underlying the development of the pre-eclamptic condition. We thus compared the expression profiles in placentas from women who underwent a normal pregnancy and from women suffering from severe pre-eclampsia. In addition, we compared the expression data between the early and late onset forms of pre-eclampsia and obtained a number of potential new prognostic biomarkers for this disease.
Keywords: disease state analysis
Overall design: Placental biopsies were obtained during Caesarean section from both normotensive patients and from those with pre-eclampsia (n = 14) (early onset type; earlier than 31 weeks gestation, n = 6 and late onset type; 31 weeks gestation or later, n = 8). Pre-eclampsia was defined as a blood pressure of higher than 160/110 mmHg, with proteinuria of more than 2g in a 24 hour collection. The expression profiles of approximately 47,669 genes were analyzed using a Whole Human Genome Oligo Microarray Kit (Agilent Technologies). A total of 10 placentas from women with pre-eclampsia and four from normal subjects were used in the hybridizations. Reverse transcription labeling and hybridization was performed using the protocol recommended by the manufacturer. The microarray experiments were then carried out using competitive hybridization experiments with Cy3 and Cy5-labeled targets; one with test placental RNAs from patients or normal control subjects, and another using pooled normal placental RNA as a template control for normalization. The glass slides were scanned using an Agilent G2565BA microarray scanner. Scanned images were then analyzed using Feature Extraction software. The average signal intensities were corrected for median background intensity and transferred with GenBank descriptors to a Microsoft Excel data spreadsheet (Microsoft, Redmond, WA). Data analysis was performed using Genespring software version 6.1 (Silicon Genetics, Redwood City, CA). After intensity dependent normalization (Lowess), the expression levels relative to the control were calculated as a ratio, and the expression profiles were then compared between each pre-eclamptic or normal sample.
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