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首页> 外文期刊>BMC Medical Genomics >An adaptive detection method for fetal chromosomal aneuploidy using cell-free DNA from 447 Korean women
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An adaptive detection method for fetal chromosomal aneuploidy using cell-free DNA from 447 Korean women

机译：使用447名韩国女性的无细胞DNA进行胎儿染色体非整倍性的自适应检测方法

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Background Noninvasive prenatal testing (NIPT) using massively parallel sequencing of cell-free DNA (cfDNA) is increasingly being used to predict fetal chromosomal abnormalities. However, concerns over erroneous predictions which occur while performing NIPT still exist in pregnant women at high risk for fetal aneuploidy. We performed the largest-scale clinical NIPT study in Korea to date to assess the risk of false negatives and false positives using next-generation sequencing. Methods A total of 447 pregnant women at high risk for fetal aneuploidy were enrolled at 12 hospitals in Korea. They underwent definitive diagnoses by full karyotyping by blind analysis and received aneuploidy screening at 11–22 weeks of gestation. Three steps were employed for cfDNA analyses. First, cfDNA was sequenced. Second, the effect of GC bias was corrected using normalization of samples as well as LOESS and linear regressions. Finally, statistical analysis was performed after selecting a set of reference samples optimally adapted to a test sample from the whole reference samples. We evaluated our approach by performing cfDNA testing to assess the risk of trisomies 13, 18, and 21 using the sets of extracted reference samples. Results The adaptive selection algorithm presented here was used to choose a more optimized reference sample, which was evaluated by the coefficient of variation (CV), demonstrated a lower CV and higher sensitivity than standard approaches. Our adaptive approach also showed that fetal aneuploidies could be detected correctly by clearly splitting the z scores obtained for positive and negative samples. Conclusions We show that our adaptive reference selection algorithm for optimizing trisomy detection showed improved reliability and will further support practitioners in reducing both false negative and positive results.
机译：背景技术使用无细胞DNA（cfDNA）大规模并行测序的无创产前检测（NIPT）越来越多地用于预测胎儿染色体异常。但是，在进行胎儿非整倍性高风险的孕妇中，仍然存在对进行NIPT时发生错误预测的担忧。迄今为止，我们在韩国进行了规模最大的NIPT临床研究，以评估使用下一代测序技术产生假阴性和假阳性的风险。方法在韩国的12家医院中，共招募了447例具有胎儿非整倍性高风险的孕妇。他们通过盲法分析进行了完整的核型分析，并在妊娠11-22周接受了非整倍性筛查，从而进行了明确的诊断。 cfDNA分析采用三个步骤。首先，对cfDNA进行测序。其次，使用样本归一化以及LOESS和线性回归校正了GC偏差的影响。最后，在从整个参考样品中选择最适合测试样品的一组参考样品后进行统计分析。我们通过执行cfDNA测试来评估我们的方法，以使用提取的参考样本集评估三体性13、18和21的风险。结果本文介绍的自适应选择算法用于选择更优化的参考样品，该参考样品通过变异系数（CV）进行了评估，与标准方法相比，具有更低的CV和更高的灵敏度。我们的自适应方法还表明，通过清楚地划分阳性和阴性样本的z评分，可以正确检测胎儿非整倍性。结论我们表明，我们用于优化三体检测的自适应参考选择算法显示出更高的可靠性，并将进一步支持从业人员减少假阴性和阳性结果。

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