Metagenomic next-generation sequencing for efficient detection of human parvovirus B19 in amniotic fluid: a case study of diagnosis and prenatal management of fetal infection
Year: 2026
Type: article
Study design: Case Report
Abstract: OBJECTIVE: Human parvovirus B19 (B19V) infection during pregnancy can lead to a range of adverse outcomes such as miscarriage, premature delivery, fetal hydrops, severe anemia, myocarditis, heart failure, and even fetal demise, posing significant risks to maternal and fetal health. The aim of this study was to establish a more efficient method for detecting B19V in amniotic fluid and to explore and optimize early diagnosis and treatment strategies for fetal B19V infection. METHODS: Intrauterine transfusion (IUT) was performed due to the occurrence of severe fetal anemia and hydrops. Amniotic fluid was obtained for genetic detection. Metagenomic next-generation sequencing (mNGS) and bioinformatic analysis were performed on the amniotic cells to identify the viral genome. RESULTS: In this study, the B19V genome was identified in the amniotic cells of the suspected case, with three viral coding sequences mapped. The coverage density reached 99.9% of the viral sequences. No other pathogen sequences, including bacteria, fungi, parasites, chlamydia, mycoplasma, rickettsia and other viruses, were identified. CONCLUSION: Our study confirmed the diagnosis of fetal B19V infection in a suspected case via amniotic fluid virus genome detection. It is the first time to exhibit the clinical application of mNGS to systematically detect the B19V genome in amniotic fluid in prenatal practice, and to achieve good results in combination with clinical management. The study highlighted the importance of comprehensive management of B19V fetal infection and demonstrated the advantages and wide application prospects of mNGS in intrauterine infection diagnosis.
Source: BMC Pregnancy and Childbirth
Authors: Ruiyu Ma, Jinling Sun, Jing Zhu, Yi Wu, Yiru Shi, Yunfan Yang, Shan Wang, Xu Han, Shuyuan Li, Li Gao, Xinrong Zhao, Renyi Hua, Yanlin Wang
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W7128015011
