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模型预测的表观遗传年龄与女性不孕症的关联。

Association of Model-Predicted Epigenetic Age and Female Infertility.

作者信息

Pozdysheva Elena, Korchagin Vitaly, Rumyantseva Tatiana, Ogneva Daria, Zhivotova Vera, Gaponova Irina, Mironov Konstantin, Akimkin Vasily

机构信息

Central Research Institute of Epidemiology Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing of Russian Federation, Moscow 111123, Russia.

Fomin Clinic, Moscow 119192, Russia.

出版信息

Epigenomes. 2025 Jun 5;9(2):19. doi: 10.3390/epigenomes9020019.

Abstract

BACKGROUND

To date, there are no precise clinical and laboratory methods to accurately predict the onset of fertility decline in women, with chronological age being the ultimate predictor. This has led to increased interest in developing methods to determine biological age, as it provides a more accurate understanding of individual age-related physiological changes.

METHODS

In this study, we developed a model for estimating biological age based on DNA methylation levels in the , , , , and genes using pyrosequencing. The model was tested in 64 Russian women, aged 25-39 years, to find an association between epigenetic age, infertility, low anti-Müllerian hormone (AMH) levels, and assisted reproductive technology (ART) failure.

RESULTS

The predictive performance of the model was evaluated. The mean absolute deviation of the model was 2.8 years; the mean absolute error was 2.6 years (R = 0.95). In the studied cohort, 33% of women exhibited epigenetic age acceleration (EAA), while 45% showed epigenetic age deceleration (EAD). All women with an EAA of ≥3 years (n = 6) had a history of infertility.

CONCLUSIONS

In this study, no statistically significant associations were observed between EAA/EAD and AMH, body mass index, infertility, or ART failure in women.

摘要

背景

迄今为止,尚无精确的临床和实验室方法能够准确预测女性生育能力下降的开始,实际年龄是最终的预测指标。这引发了人们对开发确定生物学年龄方法的兴趣增加,因为它能更准确地了解个体与年龄相关的生理变化。

方法

在本研究中,我们使用焦磷酸测序技术,基于、、、和基因中的DNA甲基化水平开发了一种估算生物学年龄的模型。该模型在64名年龄在25至39岁的俄罗斯女性中进行了测试,以寻找表观遗传年龄、不孕症、抗苗勒管激素(AMH)水平低和辅助生殖技术(ART)失败之间的关联。

结果

对该模型的预测性能进行了评估。该模型的平均绝对偏差为2.8岁;平均绝对误差为2.6岁(R = 0.95)。在研究队列中,33%的女性表现出表观遗传年龄加速(EAA),而45%表现出表观遗传年龄减速(EAD)。所有EAA≥3岁的女性(n = 6)都有不孕症病史。

结论

在本研究中,未观察到女性的EAA/EAD与AMH、体重指数、不孕症或ART失败之间存在统计学上的显著关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da40/12192080/5481751147cb/epigenomes-09-00019-g001a.jpg

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