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Observational Study
. 2025 Jul 14;23(1):99.
doi: 10.1186/s12958-025-01429-5.

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

Davide Marinello  1 , Marco Reschini  1 , Giorgia Di Stefano  1 , Giorgia Carullo  1 , Maíra Casalechi  1 , Letizia Tarantini  2   3 , Benedetta Albetti  2   3 , Valentina Bollati  2   3 , Paola Viganò  1 , Edgardo Somigliana  1   3 , Letizia Li Piani  4   5
Affiliations
Observational Study

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

Davide Marinello et al. Reprod Biol Endocrinol. .

Abstract

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.

Keywords: ART; Epigenetic clock; IVF; Infertility; Live birth; Predictor.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: All procedures were in accord with the Helsinki Declaration and all participants provided written informed consent for sample and data use. Ethical approval for the study was obtained from the local Ethical Committee (Comitato Etico Milano 1034_2022bis). Consent for publication: Not applicable. Competing interests: ES reports receiving grants from Ferring and honoraria for lectures from Merck-Serono, IBSA, and Gedeon-Richter. PV serves as co-editor of the Journal of Endometriosis and Uterine Disorders. The remaining authors declare no competing interests. Clinical trial number: Not applicable.

Figures

Fig. 1
Fig. 1
Receiver operating characteristic (ROC) curve of the live birth prediction model for ART (chronological age, AFC, AMH, epigenetic age, EPA)
Fig. 2
Fig. 2
C-statistics testing the multiparametric model to predict live birth. (with AFC on the left panel; with AMH on the right panel)
See this image and copyright information in PMC

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