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MicroRNAs secreted by human preimplantation embryos and IVF outcome

Authors :
Shintaro Kamijo
Toshio Hamatani
Hiroyuki Sasaki
Hiroki Suzuki
Akane Abe
Osamu Inoue
Maki Iwai
Seiji Ogawa
Kei Odawara
Kanako Tanaka
Mutsumi Mikashima
Masami Suzuki
Kenji Miyado
Ryo Matoba
Yasushi Odawara
Mamoru Tanaka
Source :
Reproductive Biology and Endocrinology, Vol 20, Iss 1, Pp 1-10 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract Objective To generate an effective embryo prediction model and identify a non-invasive evaluation method by analyzing microRNAs (miRNAs) in embryo culture medium. Design Analysis of microRNA profiles from spent culture medium of blastocysts with good morphology that did or did not result in pregnancy. Setting Clinical and experimental research. Patients Sixty patients who underwent thawed embryo transfer of blastocysts after intracytoplasmic sperm injection. Intervention(s) None. Main outcome measure(s) The association of miRNA abundance levels secreted by blastocysts in culture medium and implantation success. Results Our RNA sequencing analysis found a total of 53 differentially expressed miRNAs in the culture media of pregnancy and non-pregnancy groups. Twenty-one miRNAs were analyzed for their potential to predict implantation success. Eight miRNAs (hsa-miR-191-5p, hsa-miR-320a, hsa-miR-92a-3p, hsa-miR-509-3p, hsa-miR-378a-3p, hsa-miR-28-3p, hsa-miR-512-5p, and hsa-miR-181a-5p) were further extracted from the results of a logistic regression analysis of qPCR Ct values. A prediction model for high-quality blastocysts was generated using the eight miRNAs, with an average accuracy of 0.82 by 5-fold cross validation. Conclusion We isolated blastocyst miRNAs that may predict implantation success and created a model to predict viable embryos. Increasing the number of investigated cases and further studying the effect of each miRNA on embryonic development is needed to refine the miRNA-based predictive model.

Details

Language :
English
ISSN :
14777827
Volume :
20
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Reproductive Biology and Endocrinology
Publication Type :
Academic Journal
Accession number :
edsdoj.87dd0ffc1e6d4ca8962e4217c59bed39
Document Type :
article
Full Text :
https://doi.org/10.1186/s12958-022-00989-0