PGD Laboratory, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
Birth Defects Prevention and Control Institute of Guangxi Zhuang Autonomous Region, Nanning, China.
Mol Genet Genomic Med. 2024 Jan;12(1):e2293. doi: 10.1002/mgg3.2293. Epub 2023 Oct 12.
Pre-implantation genetic testing for monogenic disorders (PGT-M) is an effective approach to reducing the incidence of birth defects by preventing the transmission of inherited diseases to offspring. However, there are still controversies regarding the detection methods and transplantation of embryos. This paper aims to evaluate the effectiveness of different detection technologies applied to PGT-M through a retrospective analysis of clinical detection data.
The carrier status of pathogenic mutations and chromosomal copy number variants (CNVs) in 892 embryos was characterized using next-generation sequencing (NGS), single-nucleotide polymorphism (SNP) array, and PCR-based detection technologies. Clinical data from PGT-M cases were retrospectively analyzed to assess the effectiveness of these detection methods in identifying genetic abnormalities in embryos.
A total of 829 embryos were analyzed, with 63 being unsuccessful. Our study revealed that the success rate of detecting deletional mutations using Gap-PCR 84.9%, which is lower than that of SNP array (98.7%) and NGS (92.5%). However, no significant difference was observed when detecting point mutations using any of the methods. These findings suggest that, when detecting deletional mutations, SNP array and NGS are more suitable choices compared to Gap-PCR. While SNP array may have a lower resolution and success rate (80.5%) in analyzing CNVs compared to NGS (95.5%), it may still be useful for revealing certain abnormal types.
In conclusion, this study found that SNP analysis is advantageous for identifying polygenic and deletional mutations, whereas NGS is more cost-efficient for detecting common monogenic diseases. Additionally, SNP-based haplotyping and PCR-based direct detection of mutations can be used together to enhance the accuracy and success rates of PGT-M. Our findings offer valuable insights for PGT technicians in choosing suitable detection methods for patients.
单基因疾病的胚胎植入前遗传学检测(PGT-M)是一种通过防止遗传疾病向后代传播来降低出生缺陷发生率的有效方法。然而,对于胚胎的检测方法和移植仍存在争议。本文旨在通过回顾性分析临床检测数据,评估不同检测技术在 PGT-M 中的应用效果。
使用下一代测序(NGS)、单核苷酸多态性(SNP)芯片和基于 PCR 的检测技术,对 892 个胚胎的致病性突变和染色体拷贝数变异(CNVs)的携带状态进行了特征描述。回顾性分析 PGT-M 病例的临床数据,评估这些检测方法在识别胚胎遗传异常方面的有效性。
共分析了 829 个胚胎,其中 63 个不成功。我们的研究表明,Gap-PCR 检测缺失性突变的成功率为 84.9%,低于 SNP 芯片(98.7%)和 NGS(92.5%)。然而,在检测点突变时,任何方法之间都没有观察到显著差异。这些发现表明,在检测缺失性突变时,SNP 芯片和 NGS 比 Gap-PCR 更适合选择。虽然 SNP 芯片在分析 CNVs 方面的分辨率和成功率(80.5%)低于 NGS(95.5%),但它仍然可以用于揭示某些异常类型。
总之,本研究发现 SNP 分析有利于识别多基因和缺失性突变,而 NGS 更适合检测常见的单基因疾病。此外,基于 SNP 的单体型分析和基于 PCR 的突变直接检测可以结合使用,以提高 PGT-M 的准确性和成功率。我们的研究结果为 PGT 技术人员在为患者选择合适的检测方法提供了有价值的见解。