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An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review

  • Genetics
  • Published:
Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

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

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Data availability

All data are available upon request.

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This research was funded by FIPE-HCPA and CNPq.

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Authors and Affiliations

  1. Obstetrics/Gynecology Post-Graduate Program, Medical School, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcellos, 2350-11 andar, Porto Alegre, Rio Grande do Sul, CEP 91003-001, Brazil

    B. S. Eisele, C. Bessow, R. Donato & J. S. Cunha-Filho

  2. Hospital de Clínicas de Porto Alegre, Ob/Gyn Service, Porto Alegre, Rio Grande do Sul, Brazil

    V. K. Genro & J. S. Cunha-Filho

  3. Graduate Program in Genetics and Molecular Biology, Gene Therapy Center and Bioinformatics Core, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

    G. C. Villalba Silva

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  3. C. Bessow
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BSE and JSCF were responsible for the planning and execution of the project, data analysis, statistical analysis, and draft of the manuscript. VKG and CB were responsible for revised selected papers and ethical committee approval. JSCF and GCSV performed in silico analysis. VKG and RD revised the manuscript and participated in the final redaction.

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Eisele, B.S., Silva, G.C.V., Bessow, C. et al. An in silico model using prognostic genetic factors for ovarian response in controlled ovarian stimulation: A systematic review. J Assist Reprod Genet 38, 2007–2020 (2021). https://doi.org/10.1007/s10815-021-02141-0

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