Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application
AuthorZhou, W; Dimitriadis, E
Source TitleFrontiers in Cell and Developmental Biology
PublisherFRONTIERS MEDIA SA
AffiliationObstetrics and Gynaecology
Document TypeJournal Article
CitationsZhou, W. & Dimitriadis, E. (2020). Secreted MicroRNA to Predict Embryo Implantation Outcome: From Research to Clinical Diagnostic Application. FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 8, https://doi.org/10.3389/fcell.2020.586510.
Access StatusOpen Access
NHMRC Grant codeNHMRC/1120689
Embryo implantation failure is considered a leading cause of infertility and a significant bottleneck for in vitro fertilization (IVF) treatment. Confirmed factors that lead to implantation failure involve unhealthy embryos, unreceptive endometrium, and asynchronous development and communication between the two. The quality of embryos is further dependent on sperm parameters, oocyte quality, and early embryo development after fertilization. The extensive involvement of such different factors contributes to the variability of implantation potential across different menstrual cycles. An ideal approach to predict the implantation outcome should not compromise embryo implantation. The use of clinical material, including follicular fluid, cumulus cells, sperm, seminal exosomes, spent blastocyst culture medium, blood, and uterine fluid, that can be collected relatively non-invasively without compromising embryo implantation in a transfer cycle opens new perspectives for the diagnosis of embryo implantation potential. Compositional comparison of these samples between fertile women and women or couples with implantation failure has identified both quantitative and qualitative differences in the expression of microRNAs (miRs) that hold diagnostic potential for implantation failure. Here, we review current findings of secreted miRs that have been identified to potentially be useful in predicting implantation outcome using material that can be collected relatively non-invasively. Developing non-invasive biomarkers of implantation potential would have a major impact on implantation failure and infertility.
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