Volatile organic compounds from human skin as biomarkers of menstruation phase and severity of premenstrual syndrome: An exploratory pilot study.

Background and aim: Numerous women of reproductive age experience physical or mental discomfort during their natural menstrual cycle due to paramenstrual symptoms, such as premenstrual syndrome (PMS). To date, there is no established biomarker for the diagnosis of PMS. This study investigated the relationship between skin gas composition and menstruation cycles, and evaluated the possibility of skin gas composition as a biomarker of paramenstrual symptoms. Methods: We conducted an exploratory pilot study. Healthy Japanese women (aged 20-29 years) underwent blood and skin gas analyses on 1 day corresponding to menstruation, preovulatory, middle luteal, and late luteal phases. Skin gas was collected from the cubital fossa and armpit using a Passive Flux Sampler; samples were analyzed for 65 volatile organic compounds (VOCs) by gas chromatography-mass spectrometry (GC-MS). Non-parametric statistical analysis was performed to identify VOCs related to the menstrual cycle, levels of female hormones, and severity of PMS. Results: Fourteen women participated; of those, 12 completed the study. Regarding the relationship with the menstrual cycles, seven and four VOCs were significantly and marginally changed, respectively, at the cubital fossa during menstruation. Of those 11 compounds, 10 were also correlated with the levels of serum female hormones. At the armpit, five and three compounds were significantly and marginally changed, respectively, during menstruation. Of those eight compounds, five were also correlated with the levels of serum female hormones. In the study of PMS severity, analysis of the changes in VOCs suggested that ketones and fatty acids are increased during menstruation in the severe PMS group versus the mild PMS group. Conclusions: The results of this study suggest that certain VOCs emitted in skin gas related to the menstrual cycle, levels of female hormones, and severity of PMS. These findings may advance the metabolic understanding and development of diagnostic biomarkers for menstruation-related symptoms.