Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics

Cell-free DNA (cfDNA) is a dynamic biomarker reflecting the physiological state of the body. Its unique physical and biochemical properties, inherited from the tissue of origin, enable a wide range of clinical applications. From methylation patterns and fragmentation profiles to genetic variants, cf...

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Main Authors: Ruo Jia, Jianjiang Zhu, Feng Zhang, Yangbo Sun, Bin Zhang, Yang Du, Hong Qi
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Genetics
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Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2025.1527884/full
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author Ruo Jia
Jianjiang Zhu
Feng Zhang
Yangbo Sun
Bin Zhang
Yang Du
Hong Qi
author_facet Ruo Jia
Jianjiang Zhu
Feng Zhang
Yangbo Sun
Bin Zhang
Yang Du
Hong Qi
author_sort Ruo Jia
collection DOAJ
description Cell-free DNA (cfDNA) is a dynamic biomarker reflecting the physiological state of the body. Its unique physical and biochemical properties, inherited from the tissue of origin, enable a wide range of clinical applications. From methylation patterns and fragmentation profiles to genetic variants, cfDNA holds immense potential for diagnosing and monitoring various diseases, including cancer. In this study, we leverage a large collection of non-invasive prenatal testing (NIPT) dataset to explore the genomic landscape of fetal cfDNA, aiming to identify novel biomarkers associated with fetal development and maternal-fetal complications. Our study identifies novel fetal-specific genomic regions, further demonstrating the potential of cfDNA as a versatile biomarker. The prediction model achieved a 100% (12 of 12) positive predictive value (PPV) for hypothyroidism. Whereas for preeclampsia the PPV is much lower (25%, 3 of 12). By establishing a foundation for early hypothyroidism prediction and preeclampsia, we contribute to the expanding applications of NIPT. This approach can be adapted to explore other complex phenotypes and inform biomarker discovery, ultimately advancing maternal-fetal medicine.
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institution OA Journals
issn 1664-8021
language English
publishDate 2025-02-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Genetics
spelling doaj-art-76e1bc14795c4f2680cb5c3f7c914b972025-08-20T02:14:38ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-02-011610.3389/fgene.2025.15278841527884Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnosticsRuo Jia0Jianjiang Zhu1Feng Zhang2Yangbo Sun3Bin Zhang4Yang Du5Hong Qi6Department of Genetics, Shenyang Maternal and Child Health Hospital, Shenyang, Liaoning, ChinaPrenatal Diagnosis Center, Beijing Haidian Maternal and Child Health Hospital, Beijing, ChinaDepartment of Medical Genetics, Changzhou Maternity and Child Healthcare Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, ChinaAnnoroad Gene Technology Co., Ltd., Beijing, ChinaDepartment of Medical Genetics, Changzhou Maternity and Child Healthcare Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, ChinaAnnoroad Gene Technology Co., Ltd., Beijing, ChinaPrenatal Diagnosis Center, Beijing Haidian Maternal and Child Health Hospital, Beijing, ChinaCell-free DNA (cfDNA) is a dynamic biomarker reflecting the physiological state of the body. Its unique physical and biochemical properties, inherited from the tissue of origin, enable a wide range of clinical applications. From methylation patterns and fragmentation profiles to genetic variants, cfDNA holds immense potential for diagnosing and monitoring various diseases, including cancer. In this study, we leverage a large collection of non-invasive prenatal testing (NIPT) dataset to explore the genomic landscape of fetal cfDNA, aiming to identify novel biomarkers associated with fetal development and maternal-fetal complications. Our study identifies novel fetal-specific genomic regions, further demonstrating the potential of cfDNA as a versatile biomarker. The prediction model achieved a 100% (12 of 12) positive predictive value (PPV) for hypothyroidism. Whereas for preeclampsia the PPV is much lower (25%, 3 of 12). By establishing a foundation for early hypothyroidism prediction and preeclampsia, we contribute to the expanding applications of NIPT. This approach can be adapted to explore other complex phenotypes and inform biomarker discovery, ultimately advancing maternal-fetal medicine.https://www.frontiersin.org/articles/10.3389/fgene.2025.1527884/fullcfDNAchromatinfragmentomicsgene expressionhypothyroidismNIPT
spellingShingle Ruo Jia
Jianjiang Zhu
Feng Zhang
Yangbo Sun
Bin Zhang
Yang Du
Hong Qi
Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
Frontiers in Genetics
cfDNA
chromatin
fragmentomics
gene expression
hypothyroidism
NIPT
title Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
title_full Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
title_fullStr Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
title_full_unstemmed Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
title_short Exploration of cfDNA landscape in NIPT and clinical utilities of cfDNA based gene expression inference in prenatal diagnostics
title_sort exploration of cfdna landscape in nipt and clinical utilities of cfdna based gene expression inference in prenatal diagnostics
topic cfDNA
chromatin
fragmentomics
gene expression
hypothyroidism
NIPT
url https://www.frontiersin.org/articles/10.3389/fgene.2025.1527884/full
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