女性年龄与胚胎整倍体的复杂关系。

IF 1 Q2 Medicine
A. La Marca, M. Capuzzo, M. G. Imbrogno, V. Donno, G. Spedicato, S. Sacchi, M. Minasi, F. Spinella, P. Greco, F. Fiorentino, E. Greco
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引用次数: 6

摘要

背景女性年龄是胚胎染色体异常的最强预测因子,与胚泡整倍体率呈非线性关系:随着年龄的增长,胚泡整倍体的减少速度加快。研究发现,随着母体年龄的增长,非整倍体显著增加,从年轻女性胚胎的30%增加到40岁以上女性的70%。这种关联似乎主要是由于卵母细胞中发生的染色体异常。我们旨在利用先进的机器学习技术,为接受IVF/ICSI周期的患者建立一个胚泡整倍体率模型。方法对2014年至2016年IVF/ICSI周期进行回顾性分析。总共收集了3879个胚泡的数据进行分析。在意大利罗马欧洲医院生殖医学中心接受PGT非整倍体分析(PGT-A)的患者已被纳入分析。该方法包括全基因组扩增,然后进行阵列比较基因组杂交。为了对整倍体胚泡率进行建模,将数据分为训练集(用于拟合和校准模型)和测试集(用于评估模型的预测性能)。校准了三种不同的模型:经典线性回归;梯度提升树(GBT)机器学习模型;一个属于广义加性模型(GAM)的模型。结果本研究证实,女性年龄是胚胎染色体异常的最强预测因子,与胚泡整倍体率具有非线性关系,GBT和GAM模型很好地描述了这一关系。根据该模型,整倍体胚泡百分比的降低率随着年龄的增长而增加:37岁时的年相对变异率为-10%,45岁时为-30%。其他因素,包括男性年龄、女性和男性体重指数、受精率和卵巢储备,可能只对胚胎整倍体率产生轻微影响。结论胚胎年龄是胚胎染色体异常的最强预测因子,与胚泡整倍体率呈非线性关系。与男性和女性受试者相关的其他因素可能对这一结果的影响微乎其微。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The complex relationship between female age and embryo euploidy.
BACKGROUND Female age is the strongest predictor of embryo chromosomal abnormalities and has a non linear relationship with the blastocyst euploidy rate: with advancing age there is an acceleration in the reduction of blastocyst euploidy. Aneuploidy was found to significantly increase with maternal age from 30% in embryos from young women to 70% in women older than 40 years old. The association seems mainly due to chromosomal abnormalities occurring in the oocyte.We aimed to elaborate a model for the blastocyst euploid rate for patients undergoing IVF/ICSI cycles using advanced machine learning techniques. METHODS This was a retrospective analysis of IVF/ICSI cycles performed from 2014 to 2016. In total, data of 3879 blastocysts were collected for the analysis. Patients underwent PGT-Aneuploidy analysis (PGT-A) at the Center for Reproductive Medicine of European Hospital, Rome, Italy have been included in the analysis. The method involved whole-genome amplification followed by array comparative genome hybridization. To model the rate of euploid blastocysts, the data were split into a train set (used to fit and calibrate the models) and a test set (used to assess models' predictive performance). Three different models were calibrated: a classical linear regression; a Gradient Boosted Tree (GBT) machine learning model; a model belonging to the Generalized Additive Models (GAM). RESULTS The present study confirms that female age, which is the strongest predictor of embryo chromosomal abnormalities, and blastocyst euploidy rate have a non-linear relationship, well depicted by the GBT and the GAM models. According to this model, the rate of reduction in the percentage of euploid blastocysts increases with age: the yearly relative variation is -10% at the age of 37 and -30% at the age of 45. Other factors including male age, female and male body mass index, fertilization rate and ovarian reserve may only marginally impact on embryo euploidy rate. CONCLUSIONS Female age is the strongest predictor of embryo chromosomal abnormalities and has a non-linear relationship with the blastocyst euploidy rate. Other factors related to both the male and female subjects may only minimally affect this outcome.
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来源期刊
Minerva ginecologica
Minerva ginecologica OBSTETRICS & GYNECOLOGY-
CiteScore
3.00
自引率
0.00%
发文量
0
期刊介绍: The journal Minerva Ginecologica publishes scientific papers on obstetrics and gynecology. Manuscripts may be submitted in the form of editorials, original articles, review articles, case reports, therapeutical notes, special articles and letters to the Editor. Manuscripts are expected to comply with the instructions to authors which conform to the Uniform Requirements for Manuscripts Submitted to Biomedical Editors by the International Committee of Medical Journal Editors (www.icmje.org). Articles not conforming to international standards will not be considered for acceptance.
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