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Updated: Dec 24, 2025

Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy
Published on: August 25, 2019
Clinical Utility of a High-Resolution Melting Test for Screening Numerical Chromosomal Abnormalities in Recurrent
Yulin Zhou1, Wenyan Xu1, Yancheng Jiang2
1United Diagnostic and Research Center for Clinical Genetics, Women and Children's Hospital, School of Medicine & School of Public Health, Xiamen University, Xiamen, People's Republic of China.
Abstract:
Recurrent pregnancy loss (RPL) occurs in approximately 5% of clinically identified pregnancies. Determining the cause of RPL is essential. Genetic testing, accompanied by an evidence-based workup, is the well-accepted process for evaluating RPL; however, current genetic tests have limitations in clinical practice. We, thus, developed a high-resolution melting analysis-based test (HRM test) to screen for the most common numerical chromosomal abnormalities present in the products of conception. We examined 765 products-of-conception samples with known karyotypes retrospectively using the HRM test, which showed high technical sensitivity (96.1%) and specificity (96.3%) as well as a high positive predictive value (95.9%) for the screening of chromosomal abnormalities. The cost-effectiveness of four RPL evaluation strategies that employ different genetic tests, karyotyping, chromosomal microarray/next-generation sequencing, the HRM test, and a combination of the HRM test and chromosomal microarray/next-generation sequencing, was then compared. The costs of diagnosing an explained RPL using karyotyping or the HRM test alone were similar. Performance of the HRM screening test before chromosomal microarray/next-generation sequencing analysis improved cost-effectiveness by approximately 30%. Cost-effectiveness was more prominent in the advanced maternal age group. Thus, the HRM test could be used as an initial screening tool, followed by other diagnostic methods to improve the cost-effectiveness of RPL evaluation, or as an alternative genetic test when other methods are unavailable or unaffordable.
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