Raman spectroscopy-based metabolic fingerprinting of seminal plasma reveals distinct profiles among fertile men

Abstract

Traditional semen analysis provides valuable insights into male fertility but fails to capture the full biochemical complexity underlying sperm function. This study explored metabolic variability among fertile men using Raman spectroscopy to analyze the seminal plasma metabolome. In a cross-sectional design, semen samples were collected from 29 clinically fertile men (n = 29) and analyzed according to WHO guidelines. Metabolites were extracted using methanol/water (3:1), and Raman spectroscopy was applied to generate metabolic fingerprints of the seminal plasma. Multivariate statistical analyses, including Principal Component Analysis (PCA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), revealed two distinct metabolic subgroups among fertile men. Significant differences were identified in key biochemical features such as phenylalanine, alcohols, alkanes, aldehydes, and amides. The OPLS-DA model demonstrated excellent classification performance (R2X = 0.942, R2Y = 0.992, Q2 = 0.987), indicating robust subgroup separation and high predictive validity. These findings suggest that even within normozoospermic individuals, seminal plasma exhibits substantial metabolic heterogeneity. Raman-based metabolomic fingerprinting thus represents a promising complementary diagnostic tool to conventional semen analysis, offering deeper insight into male reproductive physiology and providing a foundation for future biomarker discovery in fertility research.