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Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

Identification of Key Molecules in Recurrent Miscarriage Based on Bioinformatics Analysis

(E-pub Ahead of Print)
Author(s): Haiwang Wu, Yan Ning , Qingying Yu, Songping Luo* and Jie Gao*

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.

Keywords: Key molecules, gene, network, recurrent miscarriage, bioinformatics analysis, pathogenesis.

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