Abstract
OBJECTIVE: Fetal growth restriction (FGR) is a severe pathological complication associated with compromised fetal development. The early diagnosis and prediction for FGR are still unclear. Sequencing technologies present a huge opportunity to identify novel biomarkers. However, limitation of individual studies (e.g., long lists of dysregulated genes, small sample size and conflicting results) hinders the selection of the best-matched ones. STUDY DESIGN: A multi-step bioinformatics analysis was performed. We separately reanalyzed data from four public RNA-seq studies, followed by a combined analysis of individual results. The differentially expressed genes (DEGs) were identified based on DESeq2. Then, function enrichment analyses and protein-protein interaction network (PPI) were conducted to screen for hub genes. The results were further verified by using external microarray data. RESULTS: A total of 65 dysregulated genes (50 down and 15 upregulated) were identified in FGR compared to controls. Function enrichment and PPI analysis revealed ten hub genes closely related to FGR. Validation analysis found four downregulated candidate biomarkers (CEACAM6, SCUBE2, DEFA4, and MPO) for FGR. CONCLUSIONS: The use of omics tools to explore mechanism of pregnancies disorders contributes to improvements in obstetric clinical practice.