Browsing by Author "Sonbol, Bayan Sameer Mohammed"

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Identifying Pathogenic Variations on Early Stage of Pregnancy Using Invasive and Non-Invasive Prenatal Samples
(2022) Sonbol, Bayan Sameer Mohammed; Borgio, Francis; AbdulAzeez, Sayed
Various factors can increase the risk of fetal genetic abnormalities during pregnancy, such as maternal age and family history. Prenatal diagnosis is a critical clinical practice for couples at risk of genetic disorders in the fetus. The study aims to identify pathogenic gene variations in the early stage of fetal development using invasive and non-invasive prenatal samples by developing fetal cell isolation, gender determination, and gene variation screening. Different samples were collected from various sources, maternal blood (n=10), serum (n=8), paternal blood (n=7), maternal buccal swab (n=8), maternal urine (n=9), and amniotic fluid (n=6). Coelomic fluid (n=1) was also collected for the first time in the history of Saudi Arabia. Different methods were used for fetal cell isolation: morphology based using a designed manual micromanipulator from invasive samples; Cluster of differentiation 71 (CD71) microbeads mediated magnetic cell sorting and percoll based subfractionation for fetal nucleated red blood cells (fNRBCs) from invasive and non-invasive samples. In-house multiplex gender PCR was used for the fetus gender determination. Nested and Amplification refractory mutation system (ARMS) PCR with newly designed primers carried out for detecting sickle cell disease (SCD) mutation (HBB:c.20A>T) in the isolated fetal cells. Our study has successfully identified a heterozygous sickle mutation in HBB gene from amniotic fluid cells and fetal DNA sample (n=3) using ARMS PCR. The study has also determined the fetal gender in single cell and fetal DNA using the gender PCR multiplex. All fetal DNA of fetal cells had a high accuracy than cell free fetal DNA (cffDNA). This study highlights that single-cell isolation from amniotic fluid and coelomic fluid could be used for accurate genetic screening for early diagnosis upon largescale validation.
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