Construction of Circulating MicroRNAs-Based Non-invasive Prediction Models of Recurrent Implantation Failure by Network Analysis

Abstract

Background: Recurrent implantation failure (RIF) is an obstacle in the process of assisted reproductive technology (ART). At present, there is limited research on its pathogenesis, diagnosis, and treatment methods. Methods and Results: In this study, a series of analytical tools were used to analyze differences in miRNAs, mRNAs, and lncRNAs in the endometrium of patients in a RIF group and a control group. Then the competing endogenous RNA (ceRNA) network was built to describe the relationship between gene regulation in the endometrium of the RIF group. Based on the results of the logistic regression of co-expression miRNAs between serum and endometrial samples, we built a predictive model based on circulating miRNAs. Conclusion: The stability and non-invasiveness of the circular miRNA prediction model provided a new method for diagnosis in RIF patients.