Weighted gene correlation network analysis reveals novel regulatory modules associated with recurrent early pregnancy loss

Autor: Xiao-na Li, Yuanqi He, Xue Li, Xiaoxiao Li, Cui-fang Hao
Rok vydání: 2020
Předmět:
0301 basic medicine
Abortion
Habitual
Cyclin E
Bioinformatics
medicine.medical_treatment
Biophysics
Gene Expression
Computational biology
Cellular defense response
Biochemistry
03 medical and health sciences
0302 clinical medicine
Predictive Value of Tests
Pregnancy
Databases
Genetic
Gene expression
Recurrent early pregnancy loss
medicine
Guanine Nucleotide Exchange Factors
Humans
Gene Regulatory Networks
Genetic Predisposition to Disease
Molecular Biology
Gene
Research Articles
Progesterone
tRNA Methyltransferases
Gene Expression & Regulation
biology
WGCNA
Gene Expression Profiling
Dock2
Growth factor
Endogenous Retroviruses
GTPase-Activating Proteins
Reproducibility of Results
Genomics
Cell Biology
Phenotype
030104 developmental biology
030220 oncology & carcinogenesis
biology.protein
Female
Signal transduction
Transcriptome
prognostic markers
Developmental Biology
Transforming growth factor
Zdroj: Bioscience Reports
ISSN: 1573-4935
0144-8463
Popis: At present, the etiology and pathogenesis of recurrent early pregnancy loss (REPL) are not completely clear. Therefore, identifying the underlying diagnostic and prognostic biomarkers of REPL can provide new ideas for the diagnosis and treatment of REPL. The chip data of REPL (GSE63901) were downloaded from the NCBI Gene Expression Omnibus (GEO) database. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to construct a co-expression module for studying the relationship between gene modules and clinical features. In addition, functional analysis of hub genes in modules of interest was performed. A total of 23 co-expression modules were identified, two of which were most significantly associated with three clinical features. The MEbrown module was positively correlated with cyclin E level and the out-of-phase trait while the MEred module was positively correlated with the effect of progesterone. We identified 17 hub genes in the MEred module. The functional enrichment analysis indicated that such hub genes were mainly involved in pathways related to cellular defense response and natural killer (NK) cell-mediated cytotoxicity. In the MEbrown module, we identified 19 hub genes, which were mainly enriched in cell adhesion molecule production, regulation of cellular response to growth factor stimulus, epithelial cell proliferation, and transforming growth factor-β (TGF-β) signaling pathway. In addition, the hub genes were validated by using other datasets and three true hub genes were finally obtained, namely DOCK2 for the MEred module, and TRMT44 and ERVMER34-1 for the MEbrown module. In conclusion, our results screened potential biomarkers that might contribute to the diagnosis and treatment of REPL.
Databáze: OpenAIRE
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