Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome

Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome

Abstract Non-invasive prenatal testing (NIPT) has been endorsed by the American College of Medical Genetics and Genomics as the preferred method for screening fetal 22q11.2 deletion syndrome (22q11.2 DS). Maternal genomic aberrations represent a significant source of false positives in NIPT, and the...

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Main Authors: Jiale Xiang, Xiangzhong Sun, Jiguang Peng, Hongfu Zhang, Jiankun Shen, Jingrou Li, Hongyu Li, Lanping Hu, Jingjing Zhang, Shihao Zhou, Sihu Xu, Yun Yang, Jun He, Zhiyu Peng
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
NIPT
22q11.2 deletion syndrome
Maternal CNV
False positive
Positive predictive value
Online Access:https://doi.org/10.1038/s41598-025-10446-8
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Summary:Abstract Non-invasive prenatal testing (NIPT) has been endorsed by the American College of Medical Genetics and Genomics as the preferred method for screening fetal 22q11.2 deletion syndrome (22q11.2 DS). Maternal genomic aberrations represent a significant source of false positives in NIPT, and there are currently no solutions that effectively address this challenge. We have devised an innovative NIPT bioinformatics pipeline designed to discern the origins of copy number variations (CNVs). Then, we recruited a cohort of 39cases of 22q11.2 DS to validate the effectiveness of our methodology. Follow-up tests including amniocentesis and genome sequencing of maternal leukocytes were conducted. Leveraging a dataset of over 900 CNVs, we developed a new pipeline that classifies CNVs into those of fetal, maternal, and maternal-fetal origin based on NIPT data. The use of our pipeline led to a notable increase in the positive predictive value of NIPT for detecting 22q11.2 DS from 87% (34/39) to 94% (34/36). Furthermore, our approach has the potential to reduce the number of invasive tests by 8% (3/39). Our innovative and reliable bioinformatics pipeline has enabled the accurate differentiation of CNV origin into fetal, maternal, and maternal-fetal categories. Incorporating this pipeline into the analytical workflow could reduce false positives in NIPT results and minimize the need for invasive prenatal diagnoses.
ISSN:2045-2322

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