Title:Identification of Key Molecules in Recurrent Miscarriage Based on
Bioinformatics Analysis
Volume: 25
Issue: 10
Author(s): Haiwang Wu, Yan Ning , Qingying Yu, Songping Luo*Jie Gao*
Affiliation:
- Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou
510405, China
- Guangzhou University of Chinese Medicine, Guangzhou 510405, China
- Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou
510405, China
- Guangzhou University of Chinese Medicine, Guangzhou 510405, China
Keywords:
Key molecules, gene, network, recurrent miscarriage, bioinformatics analysis, pathogenesis.
Abstract:
Background: Recurrent Miscarriage (RM) affects 1% to 5% of couples, and the
mechanisms still stay unclear. In this study, we explored the underlying molecular mechanism and
potential molecular biomarkers of RM as well as constructed a miRNA-mRNA regulation network.
Methods: The microarray datasets GSE73025 and GSE22490, which represent mRNA and miRNA
profiles, respectively, were downloaded from the Gene Expression Omnibus (GEO) database.
Differentially Expressed Genes (DEGs) with p-value < 0.05 and fold-change > 2 were identified
while the miRNAs with p-value < 0.05 and fold-change > 1.3 were considered as significant
differentially expressed miRNAs (DEMs).
Results: A total of 373 DEGs, including 218 up-regulated genes and 155 down-regulated genes,
were identified, while 138 up-regulated and 68 down-regulated DEMs were screened out. After
functional enrichment analysis, we found GO Biological Process (BP) terms significantly enriched
in the Fc-gamma receptor signaling pathway involved in phagocytosis. Moreover, signaling
pathway analyses indicated that the neurotrophin signaling pathway (hsa04722) was the top KEGG
enrichment. 6 hub genes (FPR1, C5AR1, CCR1, ADCY7, CXCR2, NPY) were screened out to
construct a complex regulation network in RM because they had the highest degree of affecting the
network. Besides, we constructed miRNA-mRNA network between DEMs target genes and DEGs
in RM, including hsa-miR-1297- KLHL24 and hsa-miR-548a-5p-KLHL24 pairs.
Conclusion: In conclusion, the novel differentially expressed molecules in the present study could
provide a new sight to explore the pathogenesis of RM as well as potential biomarkers and
therapeutic targets for RM diagnosis and treatment.
