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...
Saved in:
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-10446-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849763579753922560 |
|---|---|
| author | 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 |
| author_facet | 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 |
| author_sort | Jiale Xiang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-751049a18c344764bc8db70a623d3f8e |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-751049a18c344764bc8db70a623d3f8e2025-08-20T03:05:22ZengNature PortfolioScientific Reports2045-23222025-07-011511910.1038/s41598-025-10446-8Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndromeJiale Xiang0Xiangzhong Sun1Jiguang Peng2Hongfu Zhang3Jiankun Shen4Jingrou Li5Hongyu Li6Lanping Hu7Jingjing Zhang8Shihao Zhou9Sihu Xu10Yun Yang11Jun He12Zhiyu Peng13BGI GenomicsBGI GenomicsBGI GenomicsBGI GenomicsBGI GenomicsBGI GenomicsHunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal UniversityHunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal UniversityHunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal UniversityHunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal UniversityBGI GenomicsBGI GenomicsHunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal UniversityBGI GenomicsAbstract 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.https://doi.org/10.1038/s41598-025-10446-8NIPT22q11.2 deletion syndromeMaternal CNVFalse positivePositive predictive value |
| spellingShingle | 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 Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome Scientific Reports NIPT 22q11.2 deletion syndrome Maternal CNV False positive Positive predictive value |
| title | Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome |
| title_full | Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome |
| title_fullStr | Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome |
| title_full_unstemmed | Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome |
| title_short | Determining the origin of genome aberrations improves the positive predictive value of NIPT for 22q11.2 deletion syndrome |
| title_sort | determining the origin of genome aberrations improves the positive predictive value of nipt for 22q11 2 deletion syndrome |
| topic | NIPT 22q11.2 deletion syndrome Maternal CNV False positive Positive predictive value |
| url | https://doi.org/10.1038/s41598-025-10446-8 |
| work_keys_str_mv | AT jialexiang determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT xiangzhongsun determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT jiguangpeng determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT hongfuzhang determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT jiankunshen determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT jingrouli determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT hongyuli determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT lanpinghu determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT jingjingzhang determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT shihaozhou determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT sihuxu determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT yunyang determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT junhe determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome AT zhiyupeng determiningtheoriginofgenomeaberrationsimprovesthepositivepredictivevalueofniptfor22q112deletionsyndrome |