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首页> 外文期刊>Balkan journal of medical genetics: BJMG >Embryo quality predictive models based on cumulus cells gene expression
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Embryo quality predictive models based on cumulus cells gene expression

机译：基于卵丘细胞基因表达的胚胎质量预测模型

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Since the introduction of in vitro fertilization (IVF) in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC) have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR)] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC) for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ?± 0.08 and the decision tree model yielded an AUC of 0.73 ?± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.
机译：自从在不育治疗的临床实践中引入体外受精（IVF）以来，一直在研究高质量胚胎的指标。根据它们所围绕的卵母细胞的发育潜力，积云细胞（CC）具有特定的基因表达谱，因此，特定的基因表达可用作生物标记。我们研究的目的是结合多种生物标志物来观察胚胎发育预测值的改善。在这项研究中，分析了来自17个IVF患者的58个CC样本。这项研究得到了斯洛文尼亚共和国国家医学伦理委员会的批准。根据胚胎质量水平，对五个基因进行了基因表达分析[定量实时聚合酶链反应（qPCR）]。测试了两个预测模型以进行胚胎质量预测：二进制逻辑模型和决策树模型。作为主要结果，采用了五个基因的基因表达水平，并计算了两个预测模型的曲线下面积（AUC）。在测试的基因中，AMHR2和LIF在高质量和低质量的胚胎之间显示出明显的表达差异。这两个基因用于构建两个预测模型：二进制逻辑模型的AUC为0.72±0.08，决策树模型的AUC为0.73±0.03。两种不同的预测模型产生了相似的预测能力，可以区分高质量和低质量的胚胎。在最终的临床决策方面，决策树模型产生了易于解释的规则，这些规则非常适用于临床实践。

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