Objective: To screen for genomic copy number variants (CNVs) in a fetus with one sibling affected with Prader-Willi syndrome using single nucleotide polymorphism (SNP) array.
Methods: The fetus and its parents were subjected to chromosomal karyotyping and SNP array analysis.
Results: A 5p15.33 microdeletions was identified in the fetus and its phenotypically normal mother with a size of 344 kb (113 576 to 457 213). The father was normal for both testing. Analysis of literature and CNVs database indicated the above CNV to be variant of unclear significance. The couple decided to continue with the pregnancy and gave birth to a healthy boy at full-term. No abnormalities were found during the follow-up.
Conclusion: This study may provide further data for the phenotype-genotype correlation of 5p15.33 microdeletion, which differs from Cri du Chat syndrome.
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http://dx.doi.org/10.3760/cma.j.issn.1003-9406.2017.03.023 | DOI Listing |
Nonketotic hyperglycinemia (NKH), also known as glycine encephalopathy, is a rare inherited neurometabolic disorder caused by a deficiency in the glycine cleavage enzyme system (GCS), leading to the pathological accumulation of glycine in blood and cerebrospinal fluid (CSF). This case report details a neonate presenting with central apnea, profound hypotonia, and refractory seizures, alongside prenatal findings of polyhydramnios and hiccup-like fetal movements, all strongly suggestive of severe NKH. Diagnostic evaluation confirmed markedly elevated glycine levels in serum and CSF, with a CSF-to-plasma glycine ratio exceeding 0.
View Article and Find Full Text PDFPrenat Diagn
January 2025
The Genetics Institute and Genomics Center, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
N Engl J Med
December 2024
From the Prenatal Genomics and Therapy Section, Center for Precision Health Research (A.E.T., D.W.B.), and the Section on Social Network Methods, Social and Behavioral Research Branch (J.L.), National Human Genome Research Institute, the Women's Malignancies Branch (C.M.A., I.S.G., P.S.R.) and the Cancer Data Science Laboratory (P.S.R.), Center for Cancer Research, National Cancer Institute, Radiology and Imaging Sciences, Clinical Center (A.A.M., B.R.), and the Office of the Director, Eunice Kennedy Shriver National Institute of Child Health and Human Development (D.W.B.), National Institutes of Health, Bethesda, and Leidos Biomedical Research, Frederick (M.P.) - both in Maryland.
Background: Cell-free DNA (cfDNA) sequence analysis to screen for fetal aneuploidy can incidentally detect maternal cancer. Additional data are needed to identify DNA-sequencing patterns and other biomarkers that can identify pregnant persons who are most likely to have cancer and to determine the best approach for follow-up.
Methods: In this ongoing study we performed cancer screening in pregnant or postpartum persons who did not perceive signs or symptoms of cancer but received unusual clinical cfDNA-sequencing results or results that were nonreportable (i.
Curr Opin Obstet Gynecol
December 2024
Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Vanderbilt University School of Medicine, Medical Center North.
Purpose Of Review: A life-limiting fetal diagnosis (LLD) refers to a medical condition identified during pregnancy that is expected to lead to stillbirth, preclude ex utero survival, or significantly reduce neonatal life expectancy. The terms 'lethal' or 'life-limiting' are used to prognosticate early death for various anatomic or physiologic causes, although the expected timeframe is nonspecific. The purpose of this manuscript is to review how the terms 'lethal' or 'life limiting' are used in contemporary perinatal research.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Xueyuan Blvd, Nanshan, Shenzhen, Guangdong, China.
Background: Early diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane localization in three-dimensional(3D) ultrasound during the first trimester.
Methods: This retrospective study included 418 (394 normal, 24 CLP) 3D ultrasound from 288 pregnant woman between July 2022 to October 2024 from Shenzhen Guangming District People's Hospital during the 11-13 weeks of pregnancy.
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