FemiClock: Non-invasive Tools Development (Salivary and Hair Progesterone) for Ovulation Detection in Heathy Women With Regular Menstrual Cycles Without Contraception.

FemiClock: Modeling Daily and Reproductive Parameters in Women: Proof of Concept and Feasibility of Analytical Methods for the Study of Female Fertility.

Currently, the gold standard to confirm ovulation is measuring LH and/or progesterone in blood.

However, because confirmation requires a blood sample, this approach is not suitable for epidemiological studies evaluating the impact of various factors on ovulation.

Additionally, in cases of irregular menstrual cycles, there is additional difficulty in determining when the blood sample should be taken.

Our objective is the development of non-invasive markers of ovulation (salivary and hair progesterone) in women with regular menstrual cycles over a period of 3 menstrual cycles. Our hypothesis is that there is a correlation between ovulation detection, using the "gold standard" i.e. detection of the pre-ovulatory LH surge associated with an increase in progesterone during the mid-luteal phase, and the mean level of hair progesterone measured between 2 menstrual cycles.

Various studies have shown that, to be functional, the female reproductive axis requires an intact circadian system characterized by the existence of biological clocks called "clock genes" which are expressed in 24-hour cycles. In rodent, mutations in these "clock genes" lead to irregular menstrual cycles and alterations in the preovulatory LH surge. A quantitative measurement (using quantitative RT-PCR) of clock gene expression in the oral cavity will be performed.

Since the reproductive system is also under the influence of locomotor activity and diet, all of these parameters will also be analyzed using participants' smartphones and connected smartwatches.

Inclusion Criteria:

• Women aged 18 to 40 years, with a body mass index (BMI) between 19.0 and 29.9 kg/m². (Women with low or high BMI were excluded due to extensive literature showing a negative impact of extreme BMI values on the hypothalamic-pituitary-ovarian axis.)
• Women not using hormonal contraception (or using a non-hormonal copper intrauterine device), or who discontinued hormonal contraception more than 3 months prior to enrollment and do not plan to resume contraception during the 3 study menstrual cycles.
• Women with regular menstrual cycles between 25 and 35 days, with cycle length variability (difference between shortest and longest cycle) strictly less than 7 days.
• Women owning a smartphone (to enable collection and transmission of data recorded by a study-provided smartwatch).
• Exclusive daytime workers (no night or shift work).
• Hair length greater than 5 cm from root to tip, and willingness to provide a hair sample.
• Individuals affiliated with a national health insurance system or equivalent coverage.
• Individuals able to understand the study objectives and risks and willing to provide written informed consent (dated and signed).

Exclusion Criteria:

• Known fertility disorder.
• Night work and/or shift work within the 6 months prior to enrollment (between 9:00 p.m. and 6:00 a.m.).
• Untreated endocrine disorders or gynecological conditions that may affect menstrual cycles and/or ovulation, including clinical hyperandrogenism.
• History of cancer within the past 5 years.
• History of severe psychiatric disorder.
• Current use of hormonal treatment or synthetic steroid therapy.
• Self-reported pregnancy or breastfeeding within the past 3 months.
• Participants currently in an exclusion period following participation in a previous clinical study.
• Individuals under legal protection (guardianship, curatorship, or legal safeguard).
• Inability to provide informed consent (e.g., emergency situation, cognitive or comprehension difficulties).
• Desire for pregnancy within the 3 months following enrollment. The occurrence of pregnancy will not be considered an exclusion criterion; data collected during the menstrual cycle preceding pregnancy may still be analyzed, as it reflects a fertile cycle.

Exposure to potential endocrine disruptors will not be specifically assessed due to their high environmental prevalence and the complexity of their detection.