Quantitative Proteomics and Computational Analysis Elucidate Potential Paternal Biomarkers to Distinguish Idiopathic Recurrent Pregnancy Loss from Unexplained Infertility.

Background: Recurrent Pregnancy Loss (RPL) is a complex reproductive disorder that affects 0.5–3% of couples worldwide, with nearly 40–50% of cases remaining idiopathic despite thorough evaluation. While maternal factors have been extensively studied, the molecular mechanisms underlying paternal contributions to RPL remain poorly understood. This study aimed to elucidate the molecular alterations in spermatozoa from male partners of couples with idiopathic RPL and identify potential biomarkers distinguishing RPL from Unexplained Infertility (UI) and fertile controls through high-throughput proteomic and machine learning–based analyses. Methods: Semen samples from Control (n=3), RPL (n=3) and UI (n=3) were analyzed using LC MS/MS–based quantitative proteomics. A total of 6,354 proteins were identified. Differentially expressed proteins (DEPs) were determined via the limma statistical framework, with RPL specific signatures defined through an intersection strategy. Functional and pathway enrichment analyses were performed using KEGG, and GO, from MSigDB database, followed by biomarker discovery using MetaboAnalyst 6.0 with Partial Least Squares Discriminant Analysis (PLS-DA) and Receiver Operating Characteristic (ROC) validation. Results: Proteomic profiling revealed 63 RPL-specific DEPs, including 32 upregulated and 31 downregulated proteins. Upregulated proteins were primarily involved in energy metabolism, DNA repair and cytoskeletal regulation, while downregulated proteins impaired antioxidant defence and metabolic control. PLS-DA analysis established all 63 DEPs to be good classifiers for RPL (VIP score>1). Univariate biomarker analysis further confirmed 30 of these proteins to be capable of perfectly distinguishing RPL from UI and control (AUC>1) with some of the key determinants being XRCC4, USP1, BDKRB1, GPD1L, and IQGAP1. Conclusions: This integrated proteomic and computational analysis provides the first comprehensive molecular characterization of idiopathic RPL sperm proteome. The identified RPL-specific protein panel offers promising biomarkers for diagnosis and potential therapeutic targets, emphasizing the crucial role of paternal factors in recurrent pregnancy loss.