Optimization of diagnostic strategy for non‐invasive cell‐free foetal RHD determination from maternal plasma

Abstract

Background and objectives The aim of the study was to optimize routine non‐invasive prenatal detection of fetal RHD gene from plasma of RhD‐negative pregnant women (the median of gestational age was 25 weeks, range 10–38) to detect RhD materno‐fetal incompatibility and to avoid the redundant immunoprophylaxis. Materials and methods Initially only one exon of RHD gene (exon 10) was investigated in 281 plasma samples (144 verified after delivery), in the second phase three RHD exons (5, 7, 10) were analyzed in 246 samples of plasma and maternal genomic DNA (204 verified) by real‐time PCR method. Detection of Y‐chromosomal sequence DYS‐14 and five X‐chromosomal insertion/deletion polymorphisms was used to confirm the fetal cfDNA detectability in plasma. Specific polymorphisms in RHD gene were detected by sequence‐specific primer PCR in nine samples. Results When only the RHD exon 10 was tested, 2·8% of verified samples were false positive and 3·5% false negative. With three RHD exons (5, 7, 10) and maternal genomic DNA testing, only one case was false negative (0·5%). Nine samples were inconclusive due to RHD‐positive results in maternal genomic DNA. These samples were analyzed for specific mutations in RHD gene. Combination of both methods for fetal cfDNA verification succeeded in 75% of tested group. Conclusion Implementation of analysis of three RHD exons and maternal genomic DNA to routine practice lowers dramatically the ratio of false positive and negative results. This method enables more accurate determination of fetal RHD status with the reduction of unnecessary medical care and RhD immunoprophylaxis.

Gaps, Obstacles, and Opportunities in Rheumatic Heart Disease Research

“…Incorporating AI using machine learning or deep learning models can help expand the scope and reach of RHD screening especially in rural areas using lower cadre health staff thereby increasing early detection and thus reducing late presentation with severe disease and its attendant poor outcomes. 14 , 15 , 16 …”

“…For instance, focused ultrasonography using handheld devices have been used and shown to be effective in the diagnosis of RHD in the field using school children. 14 , 15 Most of those screening was done by cardiologist and people trained in echocardiography. 14 , 15 AI-enabled point of care devices or tools can help simplify the screening and diagnosis of RHD at the primary care level for use by non-cardiologists thereby reducing the workload on cardiologists and widening its reach.…”

“… 14 , 15 Most of those screening was done by cardiologist and people trained in echocardiography. 14 , 15 AI-enabled point of care devices or tools can help simplify the screening and diagnosis of RHD at the primary care level for use by non-cardiologists thereby reducing the workload on cardiologists and widening its reach. 15 , 16 …”

“…These point of care devices have the potential for allowing low-cost identification of patients at higher risk for RHD and other cardiovascular diseases potentially reducing cost of care and avoid late presentation with severe RHD in endemic regions where cardiovascular care is a luxury. 14 , 15 , 16 …”

Determination of Advantages and Limitations of qPCR Duplexing in a Single Fluorescent Channel

“…The genes of genetically modified organisms are searched in food control . Paternally inherited disease-associated sequences of DNA are investigated in the background of cell-free DNA in the plasma of pregnant females, and they are used in noninvasive prenatal diagnostics. , The correct quantification of both mixture components by qPCR is complicated once there are large differences in their representation in the mixture.…”