High-throughput longitudinal proteomics of cervicovaginal fluid during consecutive days of women's menstrual cycles: a new robust, sensitive, and efficient method

Proteomic studies of the female reproductive system have the potential to advance womens reproductive health and improve understanding of fertility-related biological processes. Cervicovaginal fluid (CVF), a complex mixture of uterine, cervical, and vaginal secretions, represents a valuable source of molecular information reflecting time-dependent molecular changes across the menstrual cycle. However, large-scale biomarker discovery in CVF remains challenging due to limitations in sensitivity, reproducibility, and data completeness in mass spectrometry-based workflows, particularly within repeated-measures longitudinal study designs. Here, we developed and evaluated a standardized high-throughput dia-PASEF-based proteomics workflow for longitudinal repeated-measures analysis of CVF samples. These samples were collected day-by-day across an ovulation-anchored 7-day window (day 0) and the subsequent six post-ovulatory days within a prospective preconception cohort (EARLY-PREG). This data-independent acquisition approach was directly compared with a conventional DDA-FracOffline strategy. Across a 7-day ovulation anchored window, DDA-FracOffline detected 2,817 quantifiable proteins, whereas dia-PASEF identified 4,229 quantifiable proteins (approximately 50% increase), with mean coefficients of variation 9.37 {+/-} 1.75% and 5.27 {+/-} 0.68%, respectively. Using day 0 (ovulation day) as the time reference for day-to-day comparisons, dia-PASEF identified higher numbers of differentially expressed proteins (DEPs) than did DDA-FracOffline across pairwise day comparisons (952-1,116 DEPs for dia-PASEF versus 161-460 DEPs for DDA-FracOffline). Pathway enrichment analyses demonstrated broader biological coverage using dia-PASEF. Furthermore, when evaluated against a literature-reported panel of clinical biomarker candidates relevant to female reproductive tract pathophysiology, the dia-PASEF workflow showed improved quantitative consistency and enhanced dynamic range sensitivity. These findings indicate that the implemented dia-PASEF approach provides a sensitive, reproducible, and scalable workflow for longitudinal repeated-measures proteomics of CVF. The method is adaptable to other biofluids and supports robust investigation of time-dependent molecular signatures associated with key biological pathways under physiologically relevant conditions in female reproductive system research.