Amniotic fluid cells could potentially be used for RNA-sequencing (seq) to help tailor clinical management of pregnancies, according to a new study. The authors say this is the first published proof-of-concept work to demonstrate the potential clinical application of this approach. Amniotic cell RNA-seq for genetic testing during pregnancy could have advantages over fibroblasts and blood.
These findings were published recently in npj Genomic Medicine. The research team comprised members from both the Departments of Paediatrics and Adolescent Medicine and that of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, the University of Hong Kong. The work was led by Brian Chung Hon-yin, Clinical Associate Professor, HKUMed.
Identifying genetic disease in a fetus can lead to better clinical management and future pregnancy planning. Current technologies for prenatal diagnosis are largely DNA-based, using gene-panel and whole-exome analysis. But a large proportion of cases (60-70%) remain undiagnosed. The global non-invasive prenatal testing market is quite advanced, and it alone is estimated to be worth more than $3.5 billion. Efforts to improve pregnancy monitoring are also underway.
Recently, it’s been shown that RNA-sequencing can increase diagnostic yield for rare genetic disease testing by 10% to 36%, however, none of these studies focused on prenatal diagnosis. In addition, while there are well-established large database cataloging the gene expression profile of different tissues for adult, there are no publicly-available datasets for amniotic fluid cells reflecting the embryological and fetal stage.
This team demonstrated the potential clinical utility of RNA-sequencing of amniotic fluid cells. A baseline for gene expression profile of amniotic fluid cells was established by performing RNA-sequencing on about 50 amniotic fluid samples. The team found that the number of well-expressed genes in amniotic fluid cells was comparable to other clinically accessible tissues commonly used for genetic diagnosis across different disease categories. Transcriptomic data obtained elucidated the molecular processes underlying the pathogenicity upgrade of variants in CHD7 and COL1A2 and revising the in silico prediction of a variant in MYRF.
The researchers also compared RNA-sequencing data of four affected fetuses with structural congenital anomalies. In collaboration with the Technical University of Munich in Germany, a bioinformatics pipeline was adapted to enhance the detection of outliers for subsequent analysis. Further in-depth curation showed that outliers can be identified in genes associated with the corresponding structural congenital anomalies in all four affected fetuses. Identifying the outliers provide more evidence at the RNA level to help diagnosis.
Findings of this study, the researchers say, could significantly help improve diagnosis of rare disease since it is the first time that amniotic fluid cells RNA-sequencing is reported to provide potential clinical utility in prenatal diagnosis. With the identification of the genetic cause, precision medicine such as tailored clinical management and preimplantation genetic diagnosis for families with family history is possible.