Objective: A novel algorithm to identify fetal microdeletion events in maternal plasma has been developed and used in clinical laboratory-based noninvasive prenatal testing. We used this approach to identify the subchromosomal events 5pdel, 22q11del, 15qdel, 1p36del, 4pdel, 11qdel, and 8qdel in routine testing. We describe the clinical outcomes of those samples identified with these subchromosomal events.

Methods: Blood samples from high-risk pregnant women submitted for noninvasive prenatal testing were analyzed using low coverage whole genome massively parallel sequencing. Sequencing data were analyzed using a novel algorithm to detect trisomies and microdeletions.

Results: In testing 175,393 samples, 55 subchromosomal deletions were reported. The overall positive predictive value for each subchromosomal aberration ranged from 60% to 100% for cases with diagnostic and clinical follow-up information. The total false positive rate was 0.0017% for confirmed false positives results; false negative rate and sensitivity were not conclusively determined.

Conclusion: Noninvasive testing can be expanded into the detection of subchromosomal copy number variations, while maintaining overall high test specificity. In the current setting, our results demonstrate high positive predictive values for testing of rare subchromosomal deletions.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034801PMC
http://dx.doi.org/10.1002/pd.4640DOI Listing

Publication Analysis

Top Keywords

noninvasive prenatal
12
prenatal testing
12
subchromosomal events
8
novel algorithm
8
subchromosomal deletions
8
positive predictive
8
subchromosomal
7
testing
7
clinical
4
clinical outcome
4

Similar Publications

Liver metastases from Gastrointestinal (GI) cancers present significant challenges in oncology, often signaling poor prognosis. Traditional detection methods like imaging and tissue biopsies have limitations in sensitivity, specificity, and tumor heterogeneity represen-tation. The advent of artificial intelligence (AI) in healthcare, driven by advancements in ma-chine learning, algorithms, and data science, offers a promising frontier for early detection and management of liver metastases.

View Article and Find Full Text PDF

Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.

Genome Res

January 2025

Center for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China;

The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation monitoring. The advent of high-throughput sequencing technologies makes it possible to scrutinize the characteristics of cfDNA molecules, opening up the fields of cfDNA genetics, epigenetics, transcriptomics, and fragmentomics, providing a plethora of biomarkers. Machine learning (ML) and/or artificial intelligence (AI) technologies that are known for their ability to integrate high-dimensional features have recently been applied to the field of liquid biopsy.

View Article and Find Full Text PDF

To evaluate the value of increasing sequencing depths of non-invasive prenatal testing (NIPT) for fetal chromosomal aneuploidies based on the semiconductor sequencing platform. This study recruited a cohort of 59,800 singleton pregnancies from Guangdong Women and Children Hospital between January 2015 and December 2020, including 48,018 cases of NIPT and 11,782 cases of expanded NIPT. Cell-free DNA from plasma samples was sequenced at a sequencing depth of 0.

View Article and Find Full Text PDF

The biochemical composition and structure of the brain are in a rapid change during the exuberant stage of fetal and neonatal development. H-MRS is a noninvasive tool that can evaluate brain metabolites in healthy fetuses and infants as well as those with neurological diseases. This review aims to provide readers with an understanding of 1) the basic principles and technical considerations relevant to H-MRS in the fetal-neonatal brain and 2) the role of H-MRS in early fetal-neonatal development brain research.

View Article and Find Full Text PDF

Visualization using NIPTviewer support the clinical interpretation of noninvasive prenatal testing results.

BMC Med Genomics

January 2025

Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, SE-751 85, Sweden.

Background: Noninvasive prenatal testing (NIPT) is increasingly used to screen for fetal chromosomal aneuploidy by analyzing cell-free DNA (cfDNA) in peripheral maternal blood. The method provides an opportunity for early detection of large genetic abnormalities without an increased risk of miscarriage due to invasive procedures. Commercial applications for use at clinical laboratories often take advantage of DNA sequencing technologies and include the bioinformatic workup of the sequence data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!