BACKGROUND: Multiple omics studies on patients with recurrent pregnancy loss (RPL) have deepened the understanding of its pathogenesis. However, few studies have combined multi-omics techniques to provide a more accurate characterization of RPL. This study aims to identify biomarkers with RPL through proteomic and transcriptomic analyses, providing new insights for its diagnosis and treatment. METHODS: Endometrial tissue samples were collected from RPL patients ( RESULTS: A total of 275 DEPs were identified between the RPL group and the normal groups. Function enrichment analyses revealed significant involvement of these DEPs in immune and inflammatory responses. LASSO analysis identified 23 hub proteins. By combining transcriptomic data, five proteins, FOSB, HPS4, MRPL34, LCAT, and TMSB10 were ultimately identified as key DEPs. The ANN model demonstrated high accuracy in distinguishing between RPL patients and normal controls, with an accuracy rate of 81.25%. CONCLUSION: Our study identified five key DEPs closely associated with RPL and revealed their promising diagnostic potential. Future validation in independent cohorts and functional studies is warranted to confirm their value as diagnostic biomarkers. CLINICAL TRIALS REGISTRY: Not applicable.
Huang et al. (Mon,) studied this question.