Epigenetic age and fertility timeline: testing an epigenetic clock to forecast in vitro fertilization success rate.

Background: In the field of in vitro fertilization (IVF), the search for reliable success predictors is ongoing, with novel biomarkers gaining increasing attention. Epigenetic clocks, mathematical models based on DNA methylation (DNAm) patterns, have revolutionized aging research by providing insights into biological aging. However, the magnitude of the benefit of the use of a simplified and non-specific epigenetic clock is still insufficient to claim for its clinical use. We investigated the potential role of epigenetic clocks in predicting IVF success.

Methods: This prospective observational study involved 379 women of reproductive age who underwent IVF treatment. On the day of recruitment, blood samples were collected, and genomic DNA was isolated from white blood cells. Epigenetic age was calculated using an algorithm based on the methylation patterns of 5 specific CpG sites and derived by pyrosequencing technique ("Zbieć-Piekarska2" model). Epigenetic age acceleration (EPA) was estimated from the residuals of a linear model, with epigenetic age regressed on chronological age. We compared the resulting epigenetic age and EPA between women who achieved a live birth and those who did not, alongside traditional ovarian reserve parameters (antral follicular count AFC; anti-müllerian hormone AMH).

Results: Among 379 women, 204 (54%) achieved LB. They were younger, had better ovarian reserve markers, retrieved more oocytes and had lower epigenetic age (36 ± 5 vs. 39 ± 5 years, p < 0.001) with moderate predictive power (area under the curve AUC = 0.652). After adjusting for antral follicular count (AFC), epigenetic age remained significantly associated with live birth (adjusted odds ratio OR = 0.91 per year; p < 0.001), suggesting IVF success is more likely in epigenetically younger women, beyond their ovarian reserve. This association was lost in subgroup analysis by infertility cause. In women aged 31-35, epigenetic age and EPA were the best predictors (AUC = 0.637). Combining epigenetic age with ovarian reserve markers slightly improved predictive accuracy (AUC = 0.692 with AFC, 0.693 with AMH) over chronological age alone (AUC = 0.672).

Conclusions: Epigenetic clocks may enhance IVF success prediction, particularly in women between 31 and 35. Our findings support the need for further research in this area and emphasize the importance of developing epigenetic models specifically tailored to fertility outcomes.