Clinical evaluation of noninvasive prenatal testing for sex chromosome aneuploidies in 9,176 Korean pregnant women: a single-center retrospective study

Abstract

Abstract Background To evaluate the clinical significance of noninvasive prenatal testing (NIPT) for detecting fetal sex chromosome aneuploidies (SCAs) in Korean pregnant women. Methods We retrospectively analyzed NIPT data from 9,176 women with singleton pregnancies referred to the CHA Biotech genome diagnostics center. Cell-free fetal DNA (cffDNA) was extracted from maternal peripheral blood, and high-throughput massively parallel sequencing was conducted. Subsequently, the positive NIPT results for SCA were validated via karyotype and chromosomal microarray analyses. Results Overall, 46 cases were SCA positive after NIPT, including 20, 12, 8, and 6 for Turner, triple X, Klinefelter, and Jacob syndromes, respectively. Among 37 women with invasive prenatal diagnosis, 19 had true positive NIPT results. The overall positive predictive value (PPV) of NIPT for detecting SCAs was 51.35%. The PPV was 18.75% for Turner, 88.89% for triple X, 71.43% for Klinefelter, and 60.00% for Jacob’s syndromes. NIPT accuracy for detecting sex chromosome trisomies was higher than that for sex chromosome monosomy (P = 0.002). No significant correlation was observed between fetal SCA incidence and maternal age (P = 0.914), except for the borderline significance of Jacob’s syndrome (P = 0.048). No significant differences were observed when comparing NIPT and karyotyping validation for fetal SCA according to pregnancy characteristics. Conclusion Our data suggest that NIPT can reliably screen for SCAs, and it performed better in predicting sex chromosome trisomies compared with monosomy X. No correlation was observed between maternal age and fetal SCA incidence, and no association was observed between different pregnancy characteristics. The accuracy of these findings requires improvements; however, our study provides an important reference for clinical genetic counseling and further management. Larger scale studies, considering confounding factors, are required for accurate evaluation.