The increased interest in assisted reproduction through in vitro fertilization (IVF) leads to an urgent need to identify biomarkers that reliably highly predict the success of pregnancy. Despite advances in diagnostics, treatment, and IVF approaches, the 30% success rate of IVF seems insurmountable. Idiopathic infertility does not have any explanation for IVF failure especially when a patient is treated with a healthy competitive embryo capable of implantation and development. Since appropriate intercellular communication is essential after embryo implantation, the emergence of the investigation of embryonic secretome including short non-coding RNA (sncRNA) molecules is crucial. That's why biomarker identification, sncRNAs secreted during the IVF process into the blastocyst's cultivation medium, by the implementation of artificial intelligence opens the door to a better understanding of the bidirectional communication between embryonic cells and the endometrium and so the success of the IVF. This study presents a set of promising new sncRNAs which are revealed to predictively distinguish a high-quality embryo, suitable for an embryo transfer in the IVF process, from a low-quality embryo with 86% accuracy. The identified exact combination of miRNAs/piRNAs as a non-invasively obtained biomarker for quality embryo determination, increasing the likelihood of implantation and the success of pregnancy after an embryo transfer.
Keywords: IVF; biomarker; embryo selection; embryonic secretome; miRNA; piRNA.