Identification of key molecules in recurrent miscarriage based on bioinformatics analysis

Author:

Wu Haiwang1ORCID,Ning Yan2,Yu Qingying1,Luo Songping1,Gao Jie1

Affiliation:

1. Department of Gynecology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China

2. Department of Chinese Medicine, Shenzhen Maternity & Child Healthcare Hospital, Shenzhen, China

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. Conclusions: 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.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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