Proteomic Signatures for Predicting Menstrual Cycle Phases

Researchers have identified a plasma proteomic signature that can accurately predict the phase of the human menstrual cycle, according to a study published April 13, 2026, in Nature Medicine.

The study provides a systems-level atlas of menstrual cycle biology by profiling nearly 3,000 circulating plasma proteins. This analysis was conducted using data from 2,760 women participating in the UK Biobank.

The findings reveal that the menstrual cycle is accompanied by widespread changes in the circulating proteome, with 198 proteins identified as varying across the cycle. These proteins form distinct temporal patterns that align with specific menstrual phases.

Proteomic Patterns and Prediction

The proteins identified in the study include growth factors, cytokines, and reproductive hormones. The researchers found that many of these proteins are expressed in stromal and epithelial cell types and are enriched in endometrial tissue, which underscores their biological specificity to the reproductive system.

Based on these findings, the research team developed a proteomic score using 75 specific proteins. This score is capable of accurately predicting the phase of the menstrual cycle.

While the roles of follicle-stimulating hormone (FSH), luteinizing hormone (LH), progesterone, and estrogen in driving ovulation, luteal transformation, and endometrial proliferation are well established, this research highlights a broader molecular landscape.

Systemic Effects of the Menstrual Cycle

The study emphasizes that the human menstrual cycle is a complex, hormonally regulated process that extends beyond the reproductive tract. The research indicates that the cycle exerts systemic effects across multiple organ systems.

Evidence suggests that the hormonal fluctuations associated with the menstrual cycle modulate several key physiological areas, including:

• Immune function
• Metabolism
• Cardiovascular physiology

Circulating proteins serve as signals from various biological pathways and tissues, providing a dynamic readout of both systemic and local physiology.

Links to Gynecological Disorders

The large-scale proteomic analysis also identified connections between specific proteins and common reproductive disorders. The researchers linked several proteins to the following conditions:

• Endometriosis
• Leiomyoma
• Abnormal bleeding

By mapping these proteomic signatures, the work aims to inform biomarker discovery in women’s health and provide deeper insights into the molecular pathways underlying gynecological disorders.

The ability to identify these signatures in plasma may help address challenges in biomarker detection. Previous observations have noted that biomarker detection in peripheral blood samples often requires adherence to a single phase of the menstrual cycle to avoid the risk of data misinterpretation caused by cyclical bodily processes.