An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review
| Autor: | J.S. Cunha-Filho, B S Eisele, Rafaela Donato, Vanessa Krebs Genro, G C Villalba Silva, Camila Karsburg Bessow |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
In silico Gene regulatory network Computational biology Fertilization in Vitro Biology 03 medical and health sciences symbols.namesake 0302 clinical medicine Betweenness centrality Ovulation Induction Interaction network Genetics Humans Computer Simulation Gene Regulatory Networks Protein Interaction Maps Gene Genetics (clinical) 030219 obstetrics & reproductive medicine Ovary Obstetrics and Gynecology Computational Biology General Medicine Prognosis Human genetics 030104 developmental biology Bonferroni correction Reproductive Medicine Genetic marker symbols Female Developmental Biology |
| Zdroj: | J Assist Reprod Genet |
| Popis: | PURPOSE: To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF. METHODS: A systematic review and in silica model using bioinformatics. After the selection of 103 papers from a systematic review process, we performed a GRADE qualification of all included papers for evidence-based quality evaluation. We included 57 genes in the silica model using a functional protein network interaction. Moreover, the construction of protein-protein interaction network was done importing these results to Cytoscape. Therefore, a cluster analysis using MCODE was done, which was exported to a plugin BINGO to determine Gene Ontology. A p value of < 0.05 was considered significant, using a Bonferroni correction test. RESULTS: In silica model was robust, presenting an ovulation-related gene network with 87 nodes (genes) and 348 edges (interactions between the genes). Related to the network centralities, the network has a betweenness mean value = 102.54; closeness mean = 0.007; and degree mean = 8.0. Moreover, the gene with a higher betweenness was PTPN1. Genes with the higher closeness were SRD5A1 and HSD17B3, and the gene with the lowest closeness was GDF9. Finally, the gene with a higher degree value was UBB; this gene participates in the regulation of TP53 activity pathway. CONCLUSIONS: This systematic review demonstrated that we cannot use any genetic marker before controlled ovarian stimulation for IVF. Moreover, in silica model is a useful tool for understanding and finding new markers for an IVF individualization. PROSPERO: CRD42020197185 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10815-021-02141-0. |
| Databáze: | OpenAIRE |
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